Instituto Nacional De Pesquisas Da Amazônia – Inpa Programa De Pós-Graduação Em Biologia (Ecologia) – Ppg-Eco Gabriela M

INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA – INPA

PROGRAMA DE PÓS-GRADUAÇÃO EM BIOLOGIA (ECOLOGIA) – PPG-ECO

EFEITO DE FATORES HISTÓRICOS E AMBIENTAIS SOBRE A COMPOSIÇÃO E DIVERSIDADE DE ASSEMBLEIAS DE LAGARTOS NO SUDOESTE DA AMAZÔNIA BRASILEIRA

GABRIELA MARQUES PEIXOTO

Manaus, Amazonas Julho, 2019

GABRIELA MARQUES PEIXOTO

EFEITO DE FATORES HISTÓRICOS E AMBIENTAIS SOBRE A COMPOSIÇÃO E DIVERSIDADE DE ASSEMBLEIAS DE LAGARTOS NO SUDOESTE DA AMAZÔNIA BRASILEIRA

ORIENTADOR: DR. IGOR L. KAEFER Co-orientadora: Dra. Albertina P. Lima

Tese apresentada ao Instituto Nacional de Pesquisas da Amazônia como parte dos Requisitos para obtenção do título de Doutor em Biologia (Ecologia).

Manaus, Amazonas Julho, 2019

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SINOPSE

Foram investigados a composição e a influência de fatores históricos e ecológicos sobre a estruturação de assembleias de lagartos na Amazônia. Para isso, foram amostradas múltiplas unidades padronizadas distribuídas na região sudoeste da

Amazônia brasileira. Os resultados mostraram que gradientes ambientais de ordem estrutural e climática atuaram sobre a composição e riqueza funcional das assembleias de lagartos da região entre os rios Purus e Madeira. Também foram demosntrado o efeito hierárquico de fatores históricos e ambientais sobre a ocorrência e distribuição das espécies na região do alto Rio Madeira.

Palavras-chave: BR-319, heterogeneidade ambiental, Inambari, rio como barreira, Rondônia, Squamata.

Dedico ao meu filho Daniel, e aos meus pais Luiz e Tânia.

Agradecimentos

Aos meus pais por me fornecerem um porto seguro e incentivo para nunca desistir dos meus sonhos. Ao meu pequeno Daniel por ter suportado a distância e a saudade. Você é o meu bem mais precioso. Mamãe te ama muito! Aos meus orientadores Igor Kaefer e Albertina Lima por toda a paciência e apoio durante estes anos. Me sinto honrada por todos os ensinamentos que recebi. Ao Dr. Rafael de Fraga pela parceria nos manuscritos, especialmente na condução das análises estatísticas e na tradução do texto para a língua inglesa. À Dra. Fernanda Werneck e à Ariane Silva por conceder permissão para acessar a coleção herpetológica do INPA. Às amigas Sulamita Rocha e Amanda Picelli, por estarem por perto sempre que precisei de um ombro amigo. Às amigas da graduação e mestrado: Andressa, Cinthia, Patrícia, Michele, Monique, Ieda, Daniele, Rose, Jackeline, Fabiana, Aline e Aninha, que mesmo distantes fisicamente foram tão presentes com bons pensamentos, apoio e carinho. Às minhas eternas orientadoras Cristina Crispim e Jane Torelli por todo o conhecimento, amizade e parceria passados durante toda a minha trajetória acadêmica, desde os meus primeiros passos na graduação. Ao Lucas Rodrigues pela paciência, carinho, e companheirismo prestados a mim nesta reta final. Gratidão! Aos colegas de trabalho do Kaefer Lab pela parceria, crescimento mútuo e conhecimentos adquiridos ao longo destes anos. Aos amigos e vizinhos Pâmela, Hevana, Gustavo, Welynton e Lucas pelas risadas, harmonia e carinho com que me receberam. Aos amigos de Manaus: Rose, Mari, Juci, Gabriel, Luciana, Val, Vera, Renan, Sully, Carla, Suzana, Karine e Paulinha pela força de sempre. Aos meus eternos e queridos professores que fizeram parte da minha construção como indivíduo. Meu total respeito e admiração por vocês e suas trajetórias de resistência. Ao Pedro, Juruna, Jussara e a toda equipe de campo que são parte essencial desta tese. À CAPES e CNPq pela concessão das bolsas ao longo deste doutorado. Ao Programa de Pós-Graduação em Ecologia do Instituto Nacional de Pesquisas da Amazônia e todos seus funcionários. vi

Ao PRONEX FAPEAM pelo financiamento do trabalho realizado em campo.

Ao PPBio/CENBAM pela estrutura previamente montada para a realização desta pesquisa.

Ao Programa de Conservação da Vida Selvagem da Santo Antônio Energia S.A. pelo suporte logístico e financeiro.

A todos os colegas não citados, e aos muitos que emanaram suas energias e carinho. Me sinto privilegiada por tê-los em minha vida.

Minha eterna gratidão!

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Amazônia “Nos teus rios quero navegar O teu ar respirar Tua beleza contemplar Embalando os sonhos meus De ver-te sempre verdejante Parte integrante Deste país gigante Que luta para manter-te inteira Intacta, linda, majestosa Amazônia, pulmão do mundo Nossa sempre serás!”

Mazé Carvalho

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Resumo Estudos ecológicos com amostragem padronizada conduzida em ampla escala espacial podem propiciar a compreensão de padrões e processos até então desconhecidos na estruturação de assembleias megadiversas, como as Neotropicais. Nesta tese apresentamos uma análise baseada em múltiplos sítios de amostragem instalados ao longo de um transecto de aproximadamente 1000 km, no interflúvio Purus-Madeira e nas margens do Alto Rio Madeira, a fim de compreender a distribuição das assembleias de lagartos desta região. No primeiro capítulo caracterizamos a composição e abundância da assembleia de lagartos em 10 módulos de amostragem ao longo da rodovia BR-319. Contabilizamos 25 táxons pertencentes a oito famílias, distribuídas de forma heterogênea ao longo do interflúvio. Também destacamos a importância de levantamentos de fauna para futuras medidas de conservação das espécies de lagartos de regiões interfluviais frente ao crescente impacto antrópico que a Amazônia enfrenta. No segundo capítulo avaliamos como a heterogeneidade ambiental, principalmente associada às Florestas Ombrófilas Abertas e Densas da região do interflúvio Purus-Madeira, molda as assembleias de lagartos. Para isso, quantificamos as assembleias através de medidas taxonômicas e funcionais em quatorze módulos de amostragem. Observamos que fatores ambientais como o solo, vegetação e pluviosidade variam em escala biogeográfica ao longo do interflúvio e influenciam o padrão de ocorrência das espécies e riqueza funcional das assembleias. Desse modo, detectamos um padrão de substituição de espécies em larga escala moldado pela influência de filtros ambientais. No terceiro capítulo investigamos, em diferentes escalas, a influência de fatores históricos e ecológicos na estruturação das assembleias de lagartos da região do alto Rio Madeira. Para isso foram amostradas 83 parcelas ao longo das margens leste e oeste do rio. Em escala regional, o alto rio Madeira atua como uma barreira biogeográfica para 29,6% das espécies. Diferentemente, a atuação de filtros ambientais explica a estruturação das assembleias em escala local. Este estudo, pioneiro em abranger uma escala geográfica tão ampla na ecologia de lagartos amazônicos, sugere que fatores históricos e ecológicos apresentam efeitos hierárquicos na determinação da estruturação espacial das assembleias. Assim como a presente investigação, futuras pesquisas abordando diferentes escalas de acordo com métodos padronizados de amostragem prometem elucidar processos e padrões relacionados à heterogênea distribuição espacial da biodiversidade amazônica.

Historical and environmental factors on the composition and diversity of lizard assemblages in the southwest of the Brazilian Amazon

Abstract

Ecological studies with standardized sampling conducted on a large scale can provide an understanding of patterns and processes hitherto unknown in the structuring of megadiverse assemblages such as those from the Neotropics. In this thesis we present an analysis based on multiple sampling sites installed along a transect of approximately 1,000 km, in the Purus- Madeira interfluve and on the banks of the Upper Madeira River, in order to understand the distribution of the lizard assemblages of this region. In the first chapter we characterized the composition and abundance of the lizard assemblage in 10 sampling modules along the BR- 319 highway. We counted 25 taxa belonging to eight families, distributed heterogeneously along the interfluve. We also we emphasize the importance of faunal surveys for future conservation measures of the species of lizards of interfluvial regions in face of the increasing anthropic impact in Amazonia. In the second chapter we evaluated how the environmental heterogeneity, mainly associated with the Open and Dense Ombrophilous Forests of the region of the Purus-Madeira interfluve forms the lizard assemblages. For this, we quantified the assemblies through taxonomic and functional measures in fourteen sampling modules. We observed that environmental factors such as soil, vegetation and rainfall vary in biogeographic scale along the interfluve and influence the pattern of occurrence of species and functional richness of the assemblages. Thus, we detected a large-scale species substitution pattern shaped by the influence of environmental filters. In the third chapter we investigated, at different scales, the influence of historical and ecological factors in the structure of lizard assemblages in the region of the upper Madeira River. For this, 83 plots were sampled along the east and west banks of the river. At the regional level, the upper Madeira River acts as a biogeographic barrier to 29.6% of the species. In contrast, the performance of environmental filters explains the structure of the assemblages at a local scale. This study, which pioneered such a wide geographic scale in the ecology of Amazonian lizards, suggests that historical and ecological factors have hierarchical effects in determining the spatial structuring of assemblages. Such as the present investigation, future research addressing different scales according to standardized sampling methods promises to elucidate processes and patterns related to the heterogeneous spatial distribution of Amazonian biodiversity.

Sumário

Capa ...... I

Folha de rosto...... II

Sinopse ...... IV

Agradecimentos ...... VI

Resumo ...... IX

Abstract ...... XI

Lista de Tabelas ...... XI

Lista de Figuras ...... XIII

1. Introdução geral ...... 1

2. Objetivos geral e específicos ...... 4

✓ Capítulo 1. The lizards along the road BR-319 in the Purus-Madeira interfluve, Brazilian

Amazonia (Squamata, Lacertilia) ...... 5

✓ Capítulo 2. Environmental gradients affect lizard assemblage composition and functional α- diversity in Amazonia...... 29

✓ Capítulo 3. Hierarchical effects of historical and environmental factors on lizard assemblages in the upper Madeira river, Amazonian Brazil...... 72

3. Síntese ...... 122 4. Referências bibliográficas...... 124

Lista de Tabelas

Capítulo 1:

Tabela 1. Location of survey modules (M1–10) in the Purus-Madeira interfluve, Brazilian Amazonia. Tabela 2. Lizard taxa sampled throughout the modules (M1–M10) installed along the road BR- 319 and the distance sampled by module in each of the three campaigns. The symbol “+” indicates the presence of the species and “-” indicates its absence.

Capítulo 2:

Tabela S1. Environmental variables used as proxy for the wide-scale biogeographic gradient. Minimum and maximum values for each site along the Purus-Madeira interfluve. Tabela S2. List of lizard taxa found along the Purus-Madeira Interfluve. OOF= Open Ombrophilous Forest, and DOF= Dense Ombrophilous Forest.

Capítulo 3:

Tabela 1. List of lizard species sampled in the upper Madeira River, Brazil. N = total abundance per species, East and West = Madeira river banks filled with presence (1) and absence (0) data. Tabela 2. Summary of the results returned by Linear Mixed-Effects Models. The models were set up using data from the west (Teotônio, Ilha dos Búfalos and West Jirau) and east (Morrinhos and Jaci-Paraná) banks of the upper Madeira River. The models were selected by AICc Δ < 2. Shapiro-Wilk tests were applied on the residuals from each model to test normality. Bolded p-values show cases in which the null hypothesis was rejected. Tabela 3. Summary of the results returned by Linear Mixed-Effects Models. The models were set up using data from the Ilha das Pedras (west river bank) and East Jirau (east river bank) modules for test the effects of environmental gradients on lizard assemblage composition. The models were selected by AICc Δ < 2. Shapiro-Wilk tests were applied on the residuals from each model to test normality. Bolded p-values show cases in which the null hypothesis was rejected.

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Lista de Figuras

Capítulo 1:

Figura 1. Location of the study area with the surveyed modules (M1–M10) along the road BR- 319, state of Amazonas, northern Brazil; and schematic illustration of the modules from the RAPELD sampling system, composed by two 5 km-long tracks containing 5 terrestrial transects (250 meters long each). Figura 2. Lizards observed along the road BR-319 in the state of Amazonas, northern Brazil. (A) Anolis tandai (male, INPA-H 33522); (B) Anolis punctatus (male, INPA-H 33691); (C) Anolis fuscoauratus (female, INPA-H 33549); (D) Plica umbra ochrocollaris (male, INPA- H 33736); (E) Tupinambis cuzcoensis (male, INPA-H 33739); (F) Kentropyx pelviceps (male, INPA-H 33708); (G) Arthrosaura reticulata (INPA-H 33543); (H) Chatogekko amazonicus (INPA-H 33584); (I) Plica umbra umbra (male, INPA-H 33021); (J) Gonatodes humeralis (male, INPA-H 33421); (K) Ameiva ameiva (male, INPA-H 33473); (L) Anolis ortonii (INPA-H 33462); (M) Thecadactylus solimoensis (INPA-H 33373); (N) Copeoglossum nigropunctatum (INPA-H 33592; (O) Loxopholis percarinatum (INPA-H 30374). Photos by Pedro H. Leitão, Albertina P. Lima, and Gabriela M. Peixoto. Figura 3. Richness of lizards in the surveyed modules (M1–10) along the road BR-319 in the Purus-Madeira interfluve, state of Amazonas, northern Brazil.

Capítulo 2:

Figura 1. Sampling RAPELD modules along the BR-319 federal highway (M1–M11) and the upper Madeira River (M12–M15). The module M8 (in red) was not sampled because it was flooded during the rainy season. Different colors show patches of natural or anthropogenic landscapes, as detailed in the inset legend. Figura 2. Lizard assemblage composition based on abundance data from 14 sampling modules installed in the Purus-Madeira interfluve, southwestern Amazonian Brazil. Assemblage composition was summarized by the first two axes of a Principal Coordinates Analysis (PCoA) applied on a Bray-Curtis pairwise dissimilarities matrix. Note the segregation in assemblage composition between Open Ombrophilous Forest (light blue circles), and Dense Ombrophilous Forest (dark blue circles). xiii

Figura 3. Relationship between the biogeographic gradient summarizing environmental variables as a PCA axis and lizard assemblage composition (A) and taxa richness (B) sampled in 14 modules along the Purus-Madeira intefluve, southwestern Amazonian Brazil. Light blue circles = Open Ombrophilous Forest, dark blue circles = Dense Ombrophilous Forest. Figura 4. Relationship between environmental variables and lizard assemblage composition summarized by the first axis of a PCoA applied on Bray-Curtis dissimilarities among paired sampling modules along the Purus-Madeira interfluve, Amazonia. Light blue circles = Open Ombrophilous Forest, dark blue circles = Dense Ombrophilous Forest. Figura 5. Ordination of 5 km2 sampling modules along gradients of tree basal area (A) and annual precipitation (B) in southwertern Amazonia. The height of the rectangles denotes abundance of lizard individuals per taxon. Figura 6. Clustering of Gower dissimilarities in functional traits of lizards sampled in 14 modules along the Purus-Madeira interfluve, southwestern Amazonia. Figura 7. Relationships between lizard (A) functional richness (FRic) and (B) functional dispersion (FDis) with a biogeographic gradient summarizing climatic and vegetation cover variables in a PCA axis. Light blue circles = Open Ombrophilous Forest, dark blue circles = Dense Ombrophilous Forest. Figura 8. Relationships between lizard functional richness (FRic) and functional dispersion (FDis) and environmental gradients measured in 14 sampling modules along the Purus-Madeira interfluve, southwestern Amazonia. Light blue circles = Open Ombrophilous Forest, dark blue circles = Dense Ombrophilous Forest.

Capítulo 3:

Figura 1. Location of the upper Madeira River, state of Rondônia, Brazil. Five km2 sampling modules (circles) near the banks. Gray circles show modules in the Inambari endemism zone, blue circles are modules in the Rondônia endemism zone [according to 20]. The acronyms summarize sampling modules’ local names: TO = Teotônio, IB = Ilha dos Búfalos, IP = Ilha das Pedras, JL = East Jirau, JR = West Jirau, JP = Jaci-Paraná, MO = Morrinhos. In detail on the left side, the standard configuration of each module, with 14 plots (squares), 250 m-long each, distributed along a gradient of distance from the river bank (0–5,000 m).

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Figura 2. Plots ordinated according to their position on the upper Madeira River (west and east). The heights of the black rectangles are relative to species abundance values. Figura 3. Plots ordinated according to their position relative the number of trees in the west bank of the upper Madeira River, state of Rondônia, Brazil. The heights of the black rectangles are relative to species abundance values. Figura 4. Partials from a multiple linear model for the Ilha das Pedras module. Model for the effects of the elevation and sand contents in the soil on lizard assemblage composition. Assemblage composition was summarized by the first axis of an Analysis of Principal Coordinates based on abundance data of the upper Madeira River, state of Rondônia, Brazil. The shades of blue show values of sand content in the soil. Figura 5. Plots ordinated according to their position relative to a gradient of elevation in the east bank of the upper Madeira River, state of Rondônia, Brazil. The heights of the black rectangles are relative to species abundance values. Figura 6. Partials from a multiple linear model to test the effects of distance from the river bank, sand and clay contents in the soil on lizard assemblage composition. Assemblage composition was summarized by the first axis of an Analysis of Principal Coordinates based on abundance data from the East Jirau sampling module, located on the east bank of the upper Madeira River, state of Rondônia, Brazil. The shades of blue show values of sand and clay contents in the soil.

INTRODUÇÃO GERAL

O conhecimento da biodiversidade global e seus mecanismos de funcionamento tem fundamental relevância para atuações conservacionistas (Elith e Leathwick, 2009), especialmente diante da intensificação das intervenções humanas aos ecossistemas naturais e do iminente declínio na riqueza de espécies (Dixo, 2001; Cole et al. 2014; Esther et al., 2014; Bernard et al., 2014). No entanto, a biodiversidade global está distribuída de maneira irregular entre os continentes, com uma expressiva concentração de espécies na região Neotropical, a qual que se estende desde o México ao sul do continente americano (Fine et al., 2014; Pavan et al., 2016). Tal riqueza torna estas regiões primordiais para estudos ecológicos que propiciem a compreensão dos mecanismos e processos, ainda desconhecidos pela ciência, que atuam nos padrões de formação das assembleias biológicas (Fraterrigo et al., 2004; Gardner et al., 2008). Com posição de destaque na região Neotropical, a floresta Amazônica é considerada a maior e mais diversa floresta tropical úmida amplamente conectada do mundo, ocupando uma área equivalente a seis milhões de km2 ao longo de nove países da América do Sul (Haseyama e Carvalho, 2011). No Brasil, o Bioma chega a ocupar mais de 40% do território nacional, desempenhando papel importante na regulação do clima, regime hidrológico, e do estoque de carbono terrestre (Nobre, 2002; Fearnside, 2006; Balmford e Whitten, 2003). Por apresentar alta complexidade estrutural, principalmente em decorrência da dinâmica geológica e climática impostas ao bioma ao longo do tempo (Hoorn et al., 2010), a região é atualmente considerada um amplo mosaico de formações distintas, com alta heterogeneidade ambiental, o que torna essa riqueza estrutural um dos principais responsáveis pela magnitude de sua biodiversidade (Sombroek, 2000; Schietti et al., 2014). Para compreender os padrões atuais de ocorrência das espécies amazônicas, distintas hipóteses, muitas delas não mutuamente exclusivas, têm sido propostas e submetidas a testes, tais como as mudanças geomorfológicas históricas, flutuações climáticas e a atuação de barreiras à dispersão (Wallace, 1852; Haffer, 1969; Cracraft, 1985; Bush, 1994; Racheli e Racheli, 2004; Ribas e Miyaki, 2004; Wüster et al., 2005; Aleixo et al., 2006; Antonelli et al., 2009; Hoorn et al., 2010; Roddaz et al., 2010; Rossetti et al., 2014; Caputo e Soares, 2016). A distribuição de muitos táxons amazônicos coincide com os limites geográficos dos grandes interflúvios da Bacia, as denominadas áreas de endemismo (Cracraft e Prum, 1988; Gascon et al., 2000; Ron, 2000; 1

Silva et al., 2005; Ribas et al., 2012; Boubli et al., 2014; Smitth et al., 2014; Fouquet, et al., 2015), mas tal padrão não é observado para todos os grupos (Godinho e Da Silva, 2018; Santorelli et al., 2018). Desse modo, as complexas histórias evolutivas das espécies constituem um ponto primordial para a compreensão dos mecanismos pelos quais ocorrereu a diversificação e consequente acúmulo de espécies para vários grupos taxonômicos, bem como para a associação com as principais teorias biogeográficas reconhecidas acerca da evolução da paisagem amazônica (Leite e Rogers, 2013; Smith et al., 2014; Antonelli et al., 2010), já que diferentes organismos podem responder de formas distintas aos mesmos eventos (Ávila-Pires et al., 2012, Godinho e Da Silva, 2018). De fato, estudos acerca dos processos causadores da diversificação nesta região têm sugerido o envolvimento sinergístico de forças históricas e ecológicas (Hoorn et al., 2010; Losos et al., 2013; Dias-Terceiro et al., 2015; Quintero et al., 2015; Moraes et al., 2016). Processos ecológicos decorrentes de interações entre elementos bióticos e abióticos, ao longo de paisagens contínuas ou clines geográficos, podem gerar especiação mesmo na ausência de alopatria (Tuomisto e Ruokolainen, 1997). Estes mecanismos se enquadram no que conhecemos como hipótese dos gradientes (Endler, 1977), pelo qual populações tendem a diferenciar-se por meio de isolamento por distância, facilitado pelas adaptações ecológicas à heterogeneidade ambiental, como o modo de dispersão e aspectos reprodutivos (Garda et al., 2013). Mesmo dentro de cada área de endemismo as especiações ecológicas podem ocorrer (Ferrão et al., 2017), já que estas regiões se configuram como subunidades ambientais por apresentarem componentes horizontais, verticais e qualitativos que permitem a presença de diferentes microhábitats (da-Silva et al., 2005; Ximenes, 2008). Tal cenário torna regiões interfluviais sistemas promissores para a investigação da influência de filtros ecológicos na composição e estruturação espacial da biota amazônica, seja por meio de abordagens taxonômicas ou relacionadas à funcionalidade ecossistêmica dos organismos (Condit et al. 2002; Maldonado et al., 2012; Ortiz et al., 2018). Os lagartos contituem bons bioindicadores para investigar o efeito de gradientes ecológicos/ambientais, e são comumente usados em modelos ecológicos por compreender um grupo abundante, com mobilidade restrita, e com alta partilha espacial de condições e recursos (Schoener, 1974; Werneck e Colli, 2006; Werneck et al., 2009; Camargo et al., 2010). Estima-se a ocorrência de aproximadamente 158 espécies de lagartos para a Amazônia brasileira (Censo da Biodiversidade/Museu Goeldi, 2019). Porém, ao longo dos anos novas espécies são descritas ou tem suas distribuições geográficas ampliadas, o que indica que a diversidade ainda deve ser

subestimada (Rodrigues e Ávila-Pires, 2005; D'angiolella et al., 2011; Peloso et al., 2011; Murphy e Jowers, 2013; Murphy et al., 2016; Oliveira et al., 2016). Este cenário configura um desafio para a identificação dos principais padrões biogeográficos para os lagartos, já que muitas espécies apresentam elevado grau de diversidade críptica, necessitando abordagens integrativas envolvendo morfologia, ecologia, comportamento e diversidade molecular (Murphy e Jowers, 2013; Sturaro et al., 2018). Um dos principais padrões regionais observados para os lagartos amazônicos é a substituição de espécies com distribuição restrita às partes Ocidental-Oriental ou Leste-Oeste da Amazônia (Ávila-Pires, 1995; Ávila-Pires et al., 2012). Entretanto, um padrão único de distribuição geográfica para lagartos amazônicos ainda permanece desconhecido (Souza et al., 2013), e muitas lacunas precisam ser preenchidas. Localmente, o padrão de distribuição das espécies amazônicas parece estar relacionado aos aspectos da heterogeneidade dos ambientes, e diversas associações já foram descritas como determinantes na estruturação destas assembleias, como o efeito da fragmentação (Bittencourt, 2008), abertura de dossel e incidência de luz (Lobão, 2008; Moraes, 2008), densidade de árvores (Pinto, 2006; Vitt et al., 2007; Bittencourt, 2008), profundidade da serrapilheira (Pinto, 2006; Vitt et al., 2007; Bittencourt, 2008), porcentagem de argila no solo (Pinto, 2006), associação a áreas ripárias (Faria et al., 2019), altitude e inclinação do terreno (Pinto, 2006; Lobão, 2008; Moraes, 2008), além da disponibilidade de alimentos (Lobão, 2008; Moraes, 2008). No entanto, devido às concentrações destes estudos em determinadas áreas da Amazônia Central, várias localidades ainda precisam ser inventariadas e estudadas quanto aos mecanismos de montagem das assembleias, principalmente em escalas mais amplas, já que grande parte destes estudos foi limitada a pequenas e médias escalas. Considerando o incipiente conhecimento sobre os padrões de distribuição das espécies para muitas áreas da Amazônia e o avanço dos impactos antrópicos que o bioma vem enfrentando ao longo das décadas (Fearnside e Graça, 2006; Bernarde et al., 2008; Fearnside et al., 2014), esta tese, com seus três capítulos apresentados a seguir, vem ampliar o conhecimento sobre os lagartos de zonas interfluviais e compreender os mecanismos que atuam sobre as distribuições das assembleias do Interflúvio Purus-Madeira e do Alto rio Madeira. Com o emprego de um delineamento amostral de um transecto de aproximadamente 1000 km, o qual foi capaz de abranger grande parte da paisagem, e possível revelar padrões ainda inéditos relacionados à distribuição de espécies e montagem de assembleias de lagartos amazônicos.

OBJETIVOS

Objetivo geral Investigar os potenciais efeitos de fatores ecológicos e históricos sobre as assembleias de lagartos em ambientes florestais de terra firme na Amazônia.

Objetivos específicos: ✓ Capítulo 1: Caracterizar a distribuição geográfica e a abundância das espécies de lagartos presentes ao longo da rodovia BR-319 na região do Interflúvio Purus- Madeira, gerando uma listagem de espécies inédita para a região. ✓ Capítulo 2: Compreender os efeitos de gradientes ambientais de ordem estrutural e climática sobre a composição e diversidade funcional das assembleias de lagartos da região entre os rios Purus e Madeira. ✓ Capítulo 3: Testar, através de escalas espaciais hierárquicas, o efeito de fatores históricos e ambientais sobre a ocorrência e distribuição das espécies de lagartos da região do alto Rio Madeira.

Capítulo 1

Gabriela Marques Peixoto; Pedro Henrique Leitão; Igor Luis Kaefer; Albertina Pimentel Lima. 2019. The lizards along the road BR-319 in the Purus-Madeira interfluve, Brazilian Amazonia (Squamata, Lacertilia). Herpetology Notes 12: 689-697.

2 The lizards along the road BR-319 in the Purus-Madeira interfluve, Brazilian Amazonia

3 (Squamata, Lacertilia)

5 Gabriela Peixoto1, *, Pedro Leitão2, Igor L. Kaefer1,3 and Albertina P. Lima1,2

7 1 Programa de Pós-Graduação em Ecologia, Instituto Nacional de Pesquisas da Amazônia, Av.

8 André Araújo 2936, Manaus, Amazonas 69011-970, Brazil.

9 2 Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazônia, Av. André Araújo

10 2936, Manaus, Amazonas 69011-970, Brazil.

11 3 Instituto de Ciências Biológicas, Universidade Federal do Amazonas, Av. General Rodrigo Octávio

12 6200, Manaus, Amazonas 69080-900, Brazil.

13 * Corresponding author. E-mail: [email protected]

15 Abstract. Here we present data on the identity and geographic distribution of lizard taxa in the

16 Purus-Madeira interfluve, along the road BR-319 in Brazilian Amazonia. We sampled 10

17 modules located at least 40 kilometres from each other. Data collection was performed through

18 active search on vegetation and leaf-litter along 250 m-long transects, and by occasional

19 encounters. Twenty-five taxa from 16 genera and eight families were recorded. The present

20 assessment reinforces the importance of this area to the conservation of Amazonian lizards and

21 should be considered as basis for studies of ecology and environmental impact regarding lizard

22 communities in this threatened region.

24 Keywords. Amazonas, Brazil, Inambari, Reptiles, Species richness

27 Introduction

28 Despite the relevance of the Amazon Forest to the world biodiversity, studies regarding

29 the biodiversity of Amazonia are scattered in the literature, reflecting on incomplete knowledge

30 about the patterns of distribution and identity of species (Magnusson et al., 2016). Since the

31 1990s, a huge portion of the Amazon Forest has been irreversibly deforested mainly due to

32 farming and logging activities (Fearnside et al., 2009). For the year 2016, in comparison with

33 2015, it is possible to identify an advance of 29% (6,207 km²) of deforestation for the entire

34 Brazilian Amazonia (INPE, 2016).

35 Squamate reptiles are, in general, vulnerable to environmental disturbances and

36 degradation, making information about the distribution of these species essential to understand

37 and conserve the Amazonian herpetofauna (Böhm et al., 2013). The richness of lizard species

38 in the Brazilian Amazonia is estimated in 138 described species (Ribeiro-Júnior, 2015; Ribeiro-

39 Júnior and Amaral, 2016). However, this number may be underestimated because most of the

40 studies were performed on the proximity of large urban centres (Rodrigues and Ávila-Pires,

41 2005; Vitt et al., 2008; Turci and Bernarde, 2008; Ávila-Pires et al., 2018). Recent taxonomic

42 assessments indicate high cryptic diversity in Amazonian species (e.g., Ávila-Pires and

43 Hoogmoed, 2000; Peloso et al., 2011; Murphy and Jowers, 2013; Murphy et al., 2016; Ferrão

44 et al., 2016; Oliveira et al., 2016; Melo-Sampaio et al., 2018), leading to the description of new

45 species or changes in taxonomic status (e.g. Bergmann and Russell, 2007; Geurgas and

46 Rodrigues, 2010; D’Angiolella et al., 2011).

47 The Purus-Madeira interfluve, where the road BR-319 was constructed during the

48 decade of 1970, is a site of high biodiversity, both described and undescribed (Ferrão et al., 7

49 2017; Ortiz et al., 2018), located in an important endemism area called Inambari (Cracraft,

50 1985).

51 It is estimated that most of this biodiversity is threatened by the construction and recent paving

52 of part of the road, which crosses the region linking the city of Manaus, in the state of

53 Amazonas, to the city of Porto Velho, in the state of Rondônia (Fearnside and Graça, 2006).

54 Simulations to assess the impacts of the road construction associated with human settlements

55 predicted a resulting deforestation of up to 5.4 million hectares by 2050, reinforcing the need

56 of mitigating measures to avoid the loss of biological diversity (Maldonado et al., 2012). In the

57 face of such prospect of increase in the frequency of anthropic disturbances and imminent loss

58 of biodiversity, we sampled multiple standard units over a transect of 620 km in the Interfluve

59 Purus-Madeira aiming to: 1) inventory the lizards (Squamata, Lacertilia); and 2) characterize

60 the geographic distribution of the taxa within this interfluvial zone.

62 Materials and Methods

63 Study site. The research was conducted along the road BR-319, which crosses the Purus-

64 Madeira interfluve, distributed almost linearly over 620 km, from central Amazonia

65 (municipality of Careiro da Várzea, state of Amazonas) to southwest Amazonia (municipality

66 of Humaitá, state of Amazonas). The area has mainly a plane topography and the elevation

67 ranges from 30 to 50 m. Approximately 90% of the area is composed of lowland ombrophilous

68 dense forest, with occurrence of medium to large-sized trees and clean forest understory. Such

69 formation is limited to high temperatures (25°C on average,) high rainfall (well distributed

70 throughout the year), and the dry period varies from 0 to 60 days per year. In the southern region

71 of our sample (near the municipality of Humaitá), the interfluve is formed by ombrophilous

72 open forest and present more than 60 dry days per year (Maldonado et al., 2012). 8

73 We used 10 research modules installed along the BR-319 according to the RAPELD-

74 Rapid Assessments and Long-term Ecological Research (in Portuguese, Pesquisas Ecológicas

75 de Longa Duração Associadas a Levantamentos Rápidos) (Magnusson et al., 2005). These

76 modules are part of a network of permanent standardized transects installed in the Amazon by

77 Programa de Pesquisas em Biodiversidade (Biodiversity Research Program) of the Brazilian

78 Science, Technology, Innovations and Communications Ministry (Magnusson et al., 2013). The

79 10 modules are located 40 to 100 kilometres from each other (Table 1) and are composed of

80 two 5 km-long tracks (Figure 1). Each track contains 5 terrestrial transects (250 meters long)

81 with standardized distance of one km between neighbouring transects. Each transect follows the

82 contour line of the terrain, minimising the edaphic variation within the transects. The

83 coordinates were obtained through GPS Garmin GPSMAP 76CSx (Datum WGS 84).

84 Data Collection. The lizard assemblage surveys lasted from October 2010 to September 2011.

85 In order to maximize the taxa detection and to minimize false absences, we employed the visual

86 transect census method using active search both in the vegetation and in the leaf-litter (Crump

87 and Scott, 1994). In addition, we recorded occasional encounters along the transect

88 displacement in the modules. The visual transect census consisted of inspecting the

89 environment by looking for terrestrial, arboreal and semi-arboreal lizards throughout the 250 m

90 of each transect. The active search in the litter consisted of rummaging the substrate (leaf litter,

91 stems and organic matter remnants) along the transect. The sampling team consisted of one

92 researcher and one assistant properly trained for lizard sampling. Due to the logistical

93 restrictions faced in the region — difficulty of access to sections of the highway that are not

94 paved and financial costs — four modules installed closer to the municipality of Manaus (M1,

95 M2, M3, and M4) were sampled in all three campaigns, while the remaining modules were

96 sampled just during the first campaign. Campaign I occurred between October 24 and 9

97 December 5, 2010, with a total of 100 hours/observer and 312 km covered throughout the

98 sampling modules; Campaign II occurred from January 9 to 24, 2011 with 40 hours/observer

99 and 128 km of modules covered; Campaign III occurred from September 12 to 27, 2011, with

100 40 hours/observer and 135 km of modules covered. The active search in each transect had a

101 duration of one hour. Considering the displacement between transects, the daily effort varied,

102 but averaged eight hours of active search per day. The sampling was concluded after 75 days

103 of fieldwork, totalling 180 hours/observer (360 sampling hours) in the transects, with a total

104 displacement of 1,150 km within the modules, and a total of 1,234 km traveled when

105 considering the distance between the base camps and the sampling modules. The captured

106 specimens were killed with peritoneal injection of 10% lidocaine chloralhydrate, and fixed in

107 10% formaldehyde for 24 hours, subsequently transferred to 70% ethanol and deposited at the

108 herpetological collection of the Instituto Nacional de Pesquisas da Amazônia (INPA-H) in the

109 municipality of Manaus, state of Amazonas, Brazil. The identification of all taxa followed the

110 taxonomic keys available in Peters and Donoso-Barros (1970), Ávila-Pires (1995), and Vitt et

111 al. (2008). The collection licenses were granted by ICMBio/IBAMA under permits 25685 and

112 29069.

113 Results

114 Twenty- five taxa (including Plica umbra subspecies) of eight families and 16 genera

115 were sampled along the 10 modules (Figure 2; Appendix 1). The family Gymnophthalmidae

116 was represented by six taxa: Arthrosaura reticulata (O'Shaughnessy, 1881); Cercosaura argula

117 Peters, 1863; Cercosaura ocellata (Wagler, 1830); Loxopholis osvaldoi (Ávila-Pires, 1995);

118 Loxopholis percarinatum (Müller, 1923); and Tretioscincus agilis (Ruthven, 1916). The family

119 Dactyloidae was represented by five taxa: Anolis fuscoauratus D'Orbigny, 1837; Anolis ortonii

120 Cope, 1868; Anolis punctatus Daudin, 1802; Anolis tandai Ávila-Pires, 1995; and Anolis 10

121 transversalis Duméril, 1851. The family Teiidae was represented by four taxa: Ameiva ameiva

122 (Linnaeus, 1758); Kentropyx altamazonica (Cope, 1876); Kentropyx pelviceps (Cope, 1868);

123 and Tupinambis cuzcoensis Murphy, Jowers, Lehtinen, Charles, Colli, Peres, Hendry and Pyron,

124 2016. The family Sphaerodactylidae was represented by three taxa: Chatogekko amazonicus

125 (Andersson, 1918); Gonatodes hasemani (Griffin, 1917); and Gonatodes humeralis (Guichenot,

126 1855). Scincidae was represented by two taxa: Copeoglossum nigropunctatum (Spix, 1825);

127 and Varzea bistriata (Spix, 1825). Tropiduridae was represented by three taxa: Plica umbra

128 umbra (Linnaeus, 1758); Plica umbra ochrocollaris Spix, 1825; and Uranoscodon

129 superciliosus (Linnaeus,1758). The family Alopoglossidae was represented by one taxon:

130 Alopoglossus atriventris Duellman, 1973. The family Phyllodactylidae also presented one

131 taxon: Thecadactylus solimoensis Bergmann and Russell, 2007 (Table 2).

132 The locations showing the highest taxa richness were modules M1 with 15 taxa (60%

133 of the taxa) and M2 with 13 taxa (52%), followed by M3 with with 11 taxa (44%) and M10

134 with 10 taxa (40%). M4 with 9 taxa (36%), M5 with 7 taxa (28%), a and modules M8 and M9

135 with 6 taxa each (24%) (Figure 3). The modules with the lowest number of species were M06

136 and M07 with five sampled taxa (20%). The module M10 was sampled only once, but some

137 taxa were found only in this module: Cercosaura ocellata, Gonatodes hasemani, Tretioscincus

138 agilis, and Tupinambis cuzcoensis. Two taxa (Chatogekko amazonicus and Kentropyx

139 altamazonica) were recorded in all modules, whereas Ameiva ameiva was recorded in 9 out of

140 10 modules (Table 2).

141

142 Discussion

143 Variations in local species richness and composition in the Amazon Basin would rely

144 on its configuration, which is a mosaic of distinct phytophysiognomical regions (Schietti et al., 11

145 2014). Such variations also result from the different geological ages and formations among

146 distinct fractions of the basin, which leads to historical evolutionary differences among areas

147 and, consequently, their biotas (Wesselingh et al., 2010; Ortiz et al., 2018). Structural

148 complexity of the vegetation in the Madeira-Purus interfluve is strongly affected by

149 groundwater and soil characteristics (Moulatlet et al., 2014; Schietti et al. 2014), which may

150 also explain differences in faunal composition along the gradient (Marciente et al., 2015).

151 The number of taxa found in this study is consistent with other studies performed in

152 Brazilian Amazonia which recorded a minimum local richness of 22 species and a maximum

153 of 44 species of lizards per inventory area (Ávila-Pires et al., 2009; Magalhães-Silva et al.,

154 2011; Prudente et al., 2013; Ribeiro-Júnior and Amaral, 2016). Studies in the Amazonian biome

155 that showed higher species richness were carried out using complementary techniques such as

156 pitfall traps, were conducted in environments with greater habitat heterogeneity including

157 flooded and nonflooded forests, or considered seasonal variability (e.g. Waldez et al., 2013;

158 Almeida et al., 2015). In relation to the richness of lizards by modules, we can associate the

159 greater values of the modules M1–3 with the highest sampling efforts employed in these sites.

160 However, module M4 was also sampled three times and showed fewer taxa. This suggests that

161 the northernmost modules of the interfluve have richer lizard assemblages. Another relevant

162 exception is module M10, which presented a richness (10 taxa) that resembles the richness

163 found in M4 (nine taxa), although module M10 was sampled only once. This module is inserted

164 within the open ombrophylous forest phytophysiognomy, unlike the other modules that are

165 inserted within dense ombrophylous forest, and possibly has greater environmental

166 heterogeneity, which may explain the presence of exclusive taxa in this module.

167 A study carried out along Purus-Madeira interfluve in five conservation units between

168 November 2012 and November 2013 registered 26 species of lizards, distributed among 19 12

169 genera and eight families (Almeida et al., 2015). The broadest herpetological survey conducted

170 in the region was the Environmental Impact Assessment (EIA) of Jirau and Santo Antônio

171 Hydroelectric Power Plants in the state of Rondônia (upper Madeira river), with a larger number

172 of species (n = 33) recorded (Lima et al., 2004). Among the sampled species, five were not

173 observed in our study, despite the proximity of the areas: Cnemidophorus aff. lemniscatus

174 Linnaeus, 1758; Enyalioides laticeps (Guichenot, 1855); Enyalius leechii (Boulenger, 1885);

175 Kentropyx calcarata (Spix, 1825); and Plica plica (Linnaeus,1758). During the EIA of the road

176 BR-319 (UFAM/DNIT, 2009), 23 lizard species of 15 genera and six families were recorded,

177 and just four of them were not sampled in our study: Alopoglossus angulatus (Linnaeus, 1758);

178 Iphisa elegans Gray, 1851; Kentropyx calcarata; and Ptychoglossus brevifrontalis Boulenger,

179 1912. Except for Kentropyx calcarata, the absence of the above-mentioned species in our

180 survey is probably due to the active sampling method employed here (without use of pitfall and

181 funnel traps), which is not adequate to detect species with fossorial or secretive habits (Andrade

182 et al., 2013).

183 On the other hand, four species recorded in this study were not listed in the EIA

184 conducted along the BR-319 (UFAM/DNIT, 2009): Copeoglossum nigropunctatum, Leposoma

185 osvaldoi, Thecadactylus solimoensis, and Varzea bistriata. The sampling of the EIA was

186 restricted to a section of the road (km 285 to km 615). In fact, the species Thecadactylus

187 solimoensis and Varzea bistriata were previously recorded only for the lower Purus River, at

188 Piagaçu-Purus Sustainable Development Reserve, which is located 84 km distant from the

189 module 5 of our study (Waldez et al., 2013).

190 Regarding the record of Plica umbra ochrocollaris, it is known that P. umbra comprises

191 more than one independent lineage, with distinct evolutionary units along different areas of

192 endemism in the Amazon. This suggests that these lineages may represent distinct species,

193 including multiple taxa within the Purus-Madeira interfluve (Carvalho et al., 2006; Oliveira et

194 al., 2016).

195 Large body-sized species such as Dracaena guianensis (Daudin, 1802) and

196 Crocodilurus amazonicus (Spix, 1825) were not observed in the present study, probably

197 because they are associated to the environments of flooded forest (Almeida et al., 2015). Hence,

198 the sampled environments along the road BR-319 are probably not suitable to these species,

199 since most of the modules are normally installed in areas of plane topography and not subjected

200 to flooding. Landscape management and conservation strategies require an understanding of

201 species distributions. This understanding also includes predictions of species’ distributions

202 under anthropogenic impacts. These approaches are essential for the long-term maintenance of

203 the forest and its biodiversity (Fearnside et al., 2009). Amazonian lizards are likely under threat

204 because of human disturbance, given the pace of modification in the Amazon Basin and the

205 lack of public policies for the effective conservation of biodiversity (Magnusson et al., 2018).

206 The construction of roads in natural environments, such as BR 319, is an alarming scenario for

207 biological conservation because it tends to favor the illegal colonization of the region, thus

208 allowing the development of activities such as mining, illegal hunting, and land real estate

209 speculation (Laurance and Balmford, 2013). These activities may affect the local fauna,

210 especially species that respond rapidly to changes in forest cover (Ferrão et al., 2016), and

211 contribute to the high number roadkills of wild animals (Brum et al., 2018). In this context,

212 this study complements the most recent list on the distribution of lizards in the Brazilian

213 Amazon (Ribeiro-Júnior and Amaral, 2016). In addition, it reinforces the importance of the

214 Purus-Madeira interfluve for the conservation of Amazonian reptiles, a region whose

215 biodiversity is rich, with great potential for new discoveries (De-França et al., 2011; Ferrão et

216 al., 2016; De-Abreu et al., 2018). Finally, this list can be used as a basis for future ecological

217 and environmental impact studies in Amazonian lizard assemblages.

218

219 Acknowledgements. We are thankful to the Programa de Pesquisa em Biodiversidade (PPBio)

220 and Centro de Estudos Integrados da Biodiversidade Amazônica (INCT-CENBAM) for

221 logistical and infrastructural support; Programa de Apoio a Núcleos de Excelência (PRONEX-

222 FAPEAM/CNPq; grant 653/2009) for financial support; and Pedro H. Pinna, Paulo R. Melo-

223 Sampaio, and Luisa M. Diele-Viegas for insightful suggestions on the manuscript.

224

225 References

226 Almeida, A.P., Carvalho, V.T., Gordo, M. (2015): Levantamento da herpetofauna em cinco

227 Unidades de Conservação na região do Interflúvio Madeira-Purus, Estado do Amazonas. In:

228 Unidades de Conservação do Amazonas no Interflúvio Purus-Madeira: Diagnóstico

229 Biológico, p. 118–138. Gordo, M., Santos H.P., Ed., Amazonas, Brasil, EDUA.

230 Andrade, S.P.D., Santos, D.L., Kawashita-Ribeiro, R.A., Vaz-Silva, W. (2013): New records and

231 updated distribution map of Iphisa elegans Gray, 1851 (Reptilia, Gymnophthalmidae).

232 Herpetology Notes 6: 395–400.

233 Ávila-Pires, T.C.S. (1995): Lizards of Brazilian Amazonia (Reptilia: Squamata). Leiden,

234 Netherlands, Zoologische Verhandeligen.

235 Ávila-Pires, T.C.S., Hoogmoed, M.S. (2000): On two new species of Pseudogonatodes Ruthven,

236 1915 (Reptilia: Squamata: Gekkonidae), with remarks on the distribution of some other

237 sphaerodactylid lizards. Zoologische Mededelingen 73: 209–223.

238 Ávila-Pires, T.C.S., Vitt, L.J., Sartorius S.S., Zani, P.A. (2009): Squamata (Reptilia) from four

239 sites in southern Amazonia, with a biogeographic analysis of Amazonian lizards. Boletim do

240 Museu Paraense Emílio Goeldi - Ciências Naturais 4: 99–118.

241 Ávila-Pires, T.C.S., Alves-Silva, K.R. Laís B., Correa, F.S., Consenza, J.F.A. et al. (2018):

242 Changes in amphibian and reptile diversity over time in Parque Estadual do Utinga, a

243 protected area surrounded by urbanization. Herpetology Notes 11: 449–512.

244 Bergmann, P.J., Russell, A.P. (2007): Systematics and biogeography of the widespread

245 Neotropical gekkonid genus Thecadactylus (Squamata), with the description of a new cryptic

246 species. Zoological Journal of the Linnean Society 149: 339–370.

247 Brum, T.R., Santos-Filho, M., Canale, G.R., Ignácio, A.R.A. (2018): Effects of roads on the

248 vertebrates diversity of the Indigenous Territory Paresi and its surrounding. Brazilian Journal

249 of Biology 78: 125–132.

250 Böhm, M., Collen, B., Baillie, J.E., Bowles P., Chanson, J., Cox, N., Rhodin, A.G. (2013): The

251 conservation status of the world’s reptiles. Biological Conservation 157: 372–385.

252 Carvalho, V.T., Esteves, F.A.D., Diniz, V.C. (2006): Levantamento da fauna de anfíbios e répteis

253 da região do rio Copacá - Resex do Baixo Juruá. In: Plano de Manejo de Fauna da Resex do

254 Baixo Juruá, p. 57–63. Andrade, P., Carvalho, V.T., Oliveira, P.H.G., Anciães, M.,

255 Rodrigues, L., Eler, E., Ed., Amazonas, Brasil, Ibama.

256 Cracraft, J. (1985): Historical biogeography and patterns of differentiation within the South

257 American avifauna: areas of endemisms. Ornithological Monographs 36: 49-84.

258 Crump, M.L., Scott Jr., N.J. (1994): Visual encounter surveys. In: Measuring and monitoring

259 biological diversity: standard methods for Amphibians, p. 84–92. Heyer, W.R., Donnelly,

260 M.A., McDiarmid, R.W., Hayek, L.C., Foster, M.S., Ed., Washington, USA, Smithsonian

261 Institution Press. 16

262 D'angiolella, A.B., Gamble, T., Ávila-Pires, T.C., Colli, G.R., Noonan, B.P., Vitt, L.J. (2011):

263 Anolis chrysolepis Duméril and Bibron, 1837 (Squamata: Iguanidae), revisited: molecular

264 phylogeny and taxonomy of the Anolis chrysolepis species group. Bulletin of the Museum

265 of Comparative Zoology 160: 35–63.

266 De-Abreu, F.H.T., Schietti, J., Anciães, M. (2018): Spatial and environmental correlates of

267 intraspecific morphological variation in three species of passerine birds from the Purus–

268 Madeira interfluvium, Central Amazonia. Evolutionary Ecology 32: 191–214.

269 De-França, D.B., Galuch, A.V., Zuanon, J., Santo, H.M.V.E., de-Mendonça, F.P., Albernaz,

270 A.L.M. (2011): The fish fauna of streams in the Madeira-Purus interfluvial region, Brazilian

271 Amazon. Check List 7: 768–773.

272 Fearnside, P.M., Graça, P., Keizer, E.H., Maldonado, F.D., Barbosa R.I., Nogueira, E.M. (2009):

273 Modelagem de desmatamento e emissões de gases de efeito estufa na região sob influência

274 da rodovia Manaus-Porto Velho (BR-319). Revista Brasileira de Meteorologia 24: 208–233.

275 Fearnside, P.M., Graça, A.P.M.L. (2006): BR-319: Brazil’s Manaus-Porto Velho Highway and

276 the potential impact of linking the arc of deforestation to central Amazonia. Environmental

277 Management 38: 705–716.

278 Ferrão, M., Colatreli, O., Fraga, R., Kaefer, I.L., Moravec, J., Lima, A.P. (2016): High species

279 richness of Scinax treefrogs (Hylidae) in a threatened landscape revealed by an integrative

280 approach. Plos One 11: 1–16.

281 Ferrão, M., Moravec, J., Fraga, R., Almeida, A.P., Kaefer, I.L., Lima, A.P. (2017): A new species

282 of Scinax from the Purus-Madeira interfluve, Brazilian Amazonia (Anura, Hylidae). ZooKeys

283 706: 137–162.

284 Geurgas, S.R., Rodrigues, M.T. (2010): The hidden diversity of Coleodactylus amazonicus

285 (Sphaerodactylinae, Gekkota) revealed by molecular data. Molecular Phylogenetics and

286 Evolution 54: 583–593.

287 INPE (2016): Projeto DETER-B. Instituto Nacional de Pesquisas Espaciais. Available at:

288 http://www.inpe.br/cra/projetos_pesquisas/deterb.php. Accessed on 20 September 2016.

289 Laurance, W.F., Balmford, A. (2013): A global map for road building: roads are proliferating

290 across the planet. Located and designed wisely, they can help rather than harm the

291 environment. Nature 495: 308–310.

292 Lima, A.P., Keller C., Rebelo, G.H. (2004): Estudos ambientais no Rio Madeira, trecho

293 Cachoeira de Santo Antônio-Abunã (Rondônia): Herpetofauna. Relatório elaborado para

294 Furnas Centrais Elétricas S.A. como parte do Estudo de Viabilidade dos AHEs Santo Antônio

295 e Jirau, para o Aproveitamento Hidrelétrico do Rio Madeira. INPA, Manaus. Available at:

296 http://philip.inpa.gov.br/publ_livres/Dossie/Mad/Documentos%20Oficiais/Madeira_COBR

297 APE/11118-COBRAP-report.pdf. Accessed on 10 September 2017.

298 Magalhães-Silva, F., Menks, A.C., Prudente, A.L.C., Costa, J.C.L., Travassos, A.E.M., Gallatti,

299 U. (2011): Squamate Reptiles from municipality of Barcarena and surroundings, state of Pará,

300 north of Brazil. Check List 7: 220–226.

301 Magnusson W.E., Lima, A.P., Luizão, R., Luizão, F., Costa, F.R.C., Castilho, C.V., Kinupp, V.F.

302 (2005): RAPELD: a modification of the Gentry method for biodiversity surveys in long-term

303 ecological research sites. Biota Neotropica 5: 1–6.

304 Magnusson, W., Braga-Neto, R. Pezzini, F., Baccaro, F., Bergallo, H., Penha, J., Rodrigues, D.,

305 Verdade, L.M., Lima, A.P., Albernaz, A.L., Hero J., Lawson, B., Castilho, C., Drucker, D.,

306 Franklin, E., Mendonça, F., Costa, F., Galdino, G., Castley, G., Zuanon, J., Vale, J., Santos,

307 J.L.C., Luizão, R., Cintra, R., Barbosa, R.I., Lisboa, A., Koblitz, R.V., Cunha, C.N., Pontes, 18

308 A.R.M. (2013): Biodiversidade e Monitoramento Ambiental Integrado, Second edition. São

309 Paulo, Brasil, Attema Editorial.

310 Magnusson, W. E., Ishikawa, N. K., Lima, A. P., Dias, D. V., Costa, F. M., de Holanda, A. S. S.,

311 et al. (2016): A linha de véu: a biodiversidade brasileira desconhecida. Parcerias

312 Estratégicas 21: 45–60.

313 Magnusson, W.E., Grelle, C.E.V., Marques, M.C.M, Rocha, C.F.D, Dias, B., Fontana, C.S., et

314 al. (2018): Effects of brazil's political crisis on the science needed for biodiversity

315 conservation. Frontiers Ecology and Evolution 6: 163.

316 Maldonado, F.D., Keizer, E.H.W., Graça, P.M.L.A., Fearnside, P.M., Vitel, C.S. (2012): Previsão

317 temporal da distribuição espacial do desmatamento no Interflúvio Purus-Madeira até o ano

318 2050. In: Rio Purus: água, território e sociedades na Amazônia sul-ocidental, p. 183–196.

319 Sousa-Jr, W.C., Waichman, A.V., Sinisgalli, P.A.A., De Angelis, C.F., Romeiro, A.R., Ed.,

320 Goiás, Brasil, LibriMundi.

321 Marciente, R., Bobrowiec, P.E.D., Magnusson, W.E. (2015): Ground-vegetation clutter affects

322 phyllostomid bat assemblage structure in lowland Amazonian forest. PLoS One 10: 1–16.

323 Melo-Sampaio, P.R., Oliveira, R.M., Prates, I. (2018). A new nurse frog from Brazil

324 (Aromobatidae: Allobates), with data on the distribution and phenotypic variation of western

325 Amazonian species. South American Journal of Herpetology 13: 131–149.

326 Moulatlet, G.M., Costa, F.R., Rennó, C.D., Emilio, T., Schietti, J. (2014): Local hydrological

327 conditions explain floristic composition in lowland Amazonian forests. Biotropica 46: 95–

328 103.

329 Murphy, J.C., Jowers M.J. (2013) Treerunners, cryptic lizards of the Plica plica group (Squamata,

330 Sauria, Tropiduridae) of northern South America. ZooKeys 355: 49–77.

331 Murphy, J.C, Jowers, M.J., Lehtinen, R.M., Charles, S.P., Colli, G.R., Peres, A.K. Jr, et al. (2016)

332 Cryptic, sympatric diversity in Tegu lizards of the Tupinambis teguixin group (Squamata,

333 Sauria, Teiidae) and the description of three new species. PLoS One 11: 15.

334 Oliveira, D.P., Carvalho, V.T., Hrbek, T. (2016): Cryptic diversity in the lizard genus Plica

335 (Squamata): phylogenetic diversity and Amazonian biogeography. Zoologica Scripta 45: 630–

336 641.

337 Peloso, P.L.V., Pellegrino, K.C.M., Rodrigues, M.T., Ávila-Pires, T.C.S. (2011): Description

338 and Phylogenetic Relationships of a New Genus and Species of Lizard (Squamata,

339 Gymnophthalmidae) from the Amazonian Rainforest of Northern Brazil. American Museum

340 Novitates 3713: 1–24.

341 Peters, J.A., Donoso-Barros, R. (1970): Lizards and amphisbaenians. In: Catalogue of the

342 Neotropical Squamata pt: II, p. 1-293. Peters, J.A., Donoso-Barros, R, Ed., Washington, USA,

343 Bulletin of the United States National Museum.

344 Ortiz, D.A., Lima, A.P., Werneck, F.P. (2018): Environmental transition zone and rivers shape

345 intraspecific population structure and genetic diversity of an Amazonian rain forest tree frog.

346 Evolutionary Ecology 32: 359–378.

347 Prudente, A.L.C., Magalhães, F., Menks, A., Sarmento, J.F.M. (2013): Checklist of Lizards of

348 the Juruti, state of Pará, Brazil. Check List 9: 42–50.

349 Ribeiro-Júnior, M.A. (2015): Catalogue of distribution of lizards (Reptilia: Squamata) from the

350 Brazilian Amazonia. I. Dactyloidae, Hoplocercidae, Iguanidae, Leiosauridae, Polychrotidae,

351 Tropiduridae. Zootaxa 3983: 1–110.

352 Ribeiro-Júnior, M.A., Amaral S. (2016): Diversity, distribution, and conservation of lizards

353 (Reptilia: Squamata) in the Brazilian Amazonia. Neotropical Biodiversity 2: 195–421.

354 Rodrigues, M.T., Ávila-Pires, T.C.S. (2005): New lizard of the genus Leposoma (Squamata,

355 Gymnophthalmidae) from the lower Rio Negro, Amazonas, Brazil. Journal of Herpetology

356 49: 541–546.

357 Schietti, J., Emilio, T., Rennó, C.D., Drucker, D.P., Costa F.R., Nogueira A. (2014): Vertical

358 distance from drainage drives floristic composition changes in an Amazonian rainforest. Plant

359 Ecology & Diversity 7: 241–253.

360 Turci, L.C.B., Bernarde, P.S. (2008): Levantamento herpetofaunístico em uma localidade no

361 município de Cacoal, Rondônia, Brasil. Bioikos 22: 101–108.

362 UFAM/DNIT (2009): Estudo de impacto ambiental EIA-RIMA – BR-319 (km 250,0/655,7) -

363 Meio Biótico. Terceira edição. Amazonas, Brasil Available at:

364 http://licenciamento.ibama.gov.br/Rodovias/ Vol. 3 Meio Biótico > Vol. Accessed on 22

365 November 2018.

366 Vitt, L.J., Magnusson, W.E., Ávila-Pires, T.C.S., Lima, A.P. (2008): Guia de Lagartos da

367 Reserva Adolpho Ducke, Amazônia Central. Primeira edição. Manaus, Brasil, Áttema

368 Design Editorial.

369 Waldez, F., Menin, M., Vogt, R.C. (2013): Diversity of amphibians and Squamata reptilians

370 from lower Purus River Basin, Central Amazonia, Brazil. Biota Neotropica 13: 300–316.

371 Wesselingh, F.P., Hoorn, C., Kroonenberg, S.B., Antonelli, A., Lundberg, J.G., Vonhof, H.B.,

372 Hooghiemstra, H. (2010): On the origin of Amazonian landscapes and biodiversity: a

373 synthesis. In: Amazonia: landscape and species evolution: a look into the past, p. 419–431.

374 Hoorn, C., Wesselingh, F., Ed., Oxford, UK, John Wiley & Sons Ltd.

375

376

377 Table 1. Location of survey modules (M1–10) in the Purus-Madeira interfluve, Brazilian

378 Amazonia.

Location in highway Geographic coordinates Elevation

M1: Purupuru, BR-319 km 34 -3.2112°S, -59.5120°W 35 m

M2: Manaquiri, BR-319 km 100 -3.4122°S, -60.2062°W 42 m

M3: Taboca, BR-319 km 168 -4.1739°S, -60.4343°W 43 m

M4: Taquara, BR-319 km 220 -4.2234°S, -60.5655°W 47 m

M5: Igapó-açu, BR-319 km 260 -4.3634°S, -61.1501°W 52 m

M6: Orquestra, BR-319 km 300 -4.5922°S, -61.3347°W 48 m

M7: Rio Novo, BR-319 km 350 -5.1558°S, -61.5558°W 59 m

M8: Jarí, BR-319 km 450 -5.5726°S, -62.2920°W 70 m

M9: Aracá, BR-319 km 540 -6.3347°S, -62.5611°W 77 m

M10: Puruzinho, BR-319 km 620 -7.1210°S, -63.1306°W 49 m

379

380 Table 2. Lizard taxa sampled throughout the modules (M1–M10) installed along the road BR-

381 319 and the distance sampled by module in each of the three campaigns. The symbol “+”

382 indicates the presence of the species and “-” indicates its absence.

Family/ Taxa M M M M M M M M M M

1 2 3 4 5 6 7 8 9 10

ALOPOGLOSSIDAE

Alopoglossus atriventris (Duellman, 1973) - + + ------

DACTYLOIDAE

Anolis fuscoauratus D'Orbigny, 1837 + + + + + - + + - +

Anolis ortonii Cope, 1868 - - + ------

Anolis punctatus Daudin, 1802 + ------

Anolis tandai Ávila-Pires, 1995 + + + + + - + + - -

Anolis transversalis Duméril, 1851 - - + ------

GYMNOPHTHALMIDAE

Arthrosaura reticulata (O'Shaughnessy, 1881) + ------

Cercosaura argula (Peters, 1863) - + ------

Cercosaura ocellata (Wagler, 1830) ------+

Loxopholis osvaldoi Ávila-Pires, 1995 + + - - - + - + - -

Loxopholis percarinatum Müller, 1923 - + - + + - - - - -

Tretioscincus agilis (Ruthven, 1916) ------+

PHYLLODACTYLIDAE

Thecadactylus solimoensis Bergmann and Russell, + ------+

2007

SCINCIDAE

Copeoglossum nigropunctatum (Spix, 1825) + - + + - + - - - -

Varzea bistriata (Spix, 1825) + ------

SPHAERODACTYLIDAE

Chatogekko amazonicus (Andersson, 1918) + + + + + + + + + +

Gonatodes hasemani (Griffin, 1917) ------+

Gonatodes humeralis (Guichenot, 1855) + + ------+ -

TEIIDAE

Ameiva ameiva (Linnaeus, 1758) + + + + + - + + + +

Kentropyx altamazonica (Cope, 1876) + + + + + + + + - +

Kentropyx pelviceps (Cope, 1868) + + + + + - - + -

Tupinambis cuzcoensis Murphy et al., 2016 ------+

TROPIDURIDAE

Plica umbra ochrocollaris (Linnaeus, 1758) + + ------+ +

Plica umbra umbra (Linnaeus, 1758) - - + + - + - - - -

Uranoscodon superciliosum (Linnaeus,1758) + + ------+ -

First campaign (km) 27 31 33 27 27 39 36 30 32 30

Second campaign (km) 38 32 33 25 ------

Third campaign (km) 36 31 39 29 ------

Total distance sampled (km) 101 94 105 81 27 39 36 30 32 30

383

384 Figures

385 Figure 1. Location of the study area with the surveyed modules (M1–M10) along the road BR-

386 319, state of Amazonas, northern Brazil; and schematic illustration of the modules from the

387 RAPELD sampling system, composed by two 5 km-long tracks containing 5 terrestrial

388 transects (250 meters long each).

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407 Figure 2. Lizards observed along the road BR-319 in the state of Amazonas, northern Brazil.

408 (A) Anolis tandai (male, INPA-H 33522); (B) Anolis punctatus (male, INPA-H 33691); (C)

409 Anolis fuscoauratus (female, INPA-H 33549); (D) Plica umbra ochrocollaris (male, INPA-H

410 33736); (E) Tupinambis cuzcoensis (male, INPA-H 33739); (F) Kentropyx pelviceps (male,

411 INPA-H 33708); (G) Arthrosaura reticulata (INPA-H 33543); (H) Chatogekko amazonicus

412 (INPA-H 33584); (I) Plica umbra umbra (male, INPA-H 33021); (J) Gonatodes humeralis

413 (male, INPA-H 33421); (K) Ameiva ameiva (male, INPA-H 33473); (L) Anolis ortonii (INPA-

414 H 33462); (M) Thecadactylus solimoensis (INPA-H 33373); (N) Copeoglossum

415 nigropunctatum (INPA-H 33592; (O) Loxopholis percarinatum (INPA-H 30374). Photos by

416 Pedro H. Leitão, Albertina P. Lima, and Gabriela M. Peixoto. 25

417 26

418

419 Figure 3. Richness of lizards in the surveyed modules (M1–10) along the road BR-319 in the

420 Purus-Madeira interfluve, state of Amazonas, northern Brazil.

421

422

423 Appendix 1. Voucher numbers of the taxa recorded at the herpetological collection of the

424 National Institute of Amazonian Research (INPA-H).

425 Alopoglossidae: Alopoglossus atriventris (INPA-H 33600, 33601); Dactyloidae: Anolis

426 fuscoauratus (INPA-H 33480, 33482, 33494, 33516, 33530, 33531, 33536); Anolis ortonii

427 (INPA-H 33424, 33471, 33583, 33702); Anolis punctatus (INPA-H 33368, 33371, 33519,

428 33547); Anolis tandai (INPA-H 33496, 33683, 33684, 33695, 33696, 33722); Anolis

429 tranversalis (INPA-H 33640, 33641, 33642, 33643); Gymnophthalmidae: Arthrosaura

430 reticulata (INPA-H 33514, 33570, 33651, 33671, 33672); Cercosaura argula (INPA-H 33423,

431 33673, 33832); Cercosaura ocellata (INPA-H 33389, 33430, 33438, 33470, 33534, 33543);

432 Leposoma osvaldoi (INPA-H 25664, 30375, 30376); Leposoma percarinatum (INPA-H 28245,

433 28248, 30374); Tretioscincus agilis (INPA-H 28265, 33435, 33436, 33568); Phyllodactylidae:

434 Thecadactylus solimoensis (INPA-H 33373, 33381, 33386, 33413, 33414, 33418, 33433);

435 Scincidae: Copeoglossum nigropunctatum (INPA-H 33592, 33594, 33595, 33635, 33638,

436 33639); Varzea bistriata (INPA-H 33511, 33683, 33684, 33695, 33722); Sphaerodactylidae:

437 Chatogekko amazonicus (INPA-H 33445, 33447, 33448, 33449, 33451, 33452, 33456, 33457,

438 33458, 33459, 33495, 33537, 33538, 33539); Gonatodes hasemani (INPA-H 33834);

439 Gonatodes humeralis (INPA-H 33403, 33404, 33443, 33576, 33612, 33613); Teiidae: Ameiva

440 ameiva (INPA-H 33431, 33473, 33671); Kentropyx altamazonica (INPA-H 33730); Kentropyx

441 pelviceps (INPA-H 33504, 33399, 33653); Tupinambis cuscoensis (INPA-H 33739);

442 Tropiduridae: Plica umbra umbra (INPA-H 33658); Plica umbra ochrocollaris (INPA-H

443 33474, 33656, 33736); Uranoscodon superciliosus (INPA-H 33604, 33677, 33678).

Capítulo 2

Gabriela Marques Peixoto; Rafael de Fraga; Pedro Henrique Leitão; Igor Luis Kaefer; Albertina Pimentel Lima. Biogeographical gradients affect lizard assemblage composition and functional α-diversity in Amazonia. Manuscrito em preparação para Biotropica.

LRH: Peixoto et al.

RRH: Wide-Scale Spatial Structure of Lizard Assemblages

1 Biogeographical gradients affect lizard assemblage composition and functional α-

2 diversity in Amazonia

3 Gabriela Marques Peixoto1*, Rafael de Fraga2, Pedro Henrique Leitão1, Igor Luis Kaefer1,3,

4 Albertina Pimentel Lima1

5 1 Programa de Pós-Graduação em Ecologia, Instituto Nacional de Pesquisas da Amazônia, Av.

6 André Araújo 2936, Manaus, Amazonas 69011-970, Brasil.

7 2 Programa de Pós-Graduação em Recursos Naturais Amazônicos, Universidade Federal do

8 Oeste do Pará, Santarém, Pará, Brasil.

9 3 Instituto de Ciências Biológicas, Universidade Federal do Amazonas, Av. General Rodrigo

10 Octávio 6200, Manaus, Amazonas 69080-900, Brasil.

*[email protected]

Received ______; revision accepted ______. 31

11 Abstract

12 Species distributions may be influenced by ecological processes and mechanisms quantified

13 through interactions with biotic and abiotic elements. Such interactions often explain species

14 co-occurrence via ecological filtering. Here we aimed to understand how different

15 environmental gradients influence species richness, composition and functional diversity in

16 heterogeneous rainforests of Amazonia, using lizard assemblage data as a model. We sampled

17 14 sites composed of 2 main 5 km-long trails, parallel and separated by 1 km, containing five

18 250 m-long plots, distributed along 880 km along the interfluvial region between the Purus

19 and Madeira rivers, in southwestern Amazonia. We tested the general hypothesis that

20 climatic, edaphic and vegetation-cover variables cause variation in lizard assemblages along

21 the two ombrophylous forest types covering the region. We found that the environmental

22 heterogeneity covered by the sampled tropical forests predicts spatial structuring of lizard

23 assemblages. This finding is supported by distribution of taxonomic and functional diversity

24 measures across categorical (dense and open Ombrophylous forest) and continuous habitats

25 (biogeographical-scale environmental gradient and individual environmental variables). Our

26 results also highlight the importance of investigating a same assemblage dataset under

27 different dimensions of biodiversity for ecology and conservation, as well as the relevance of

28 this region as a model for community ecology studies over wider scales.

29 Key words: Brazil; environmental heterogeneity; reptiles; Squamata; tropical forest.

32 PATTERNS OF SPECIES DISTRIBUTION AT WIDE SPATIAL SCALES, SUCH AS THE AMAZON BASIN,

33 ARE OFTEN DETERMINED BY historical processes acting on habitat dynamics and structure

34 (Wiens et al. 2011, Smith et al. 2014). At narrow scales (local), species distribution is

35 primarily limited by ecological processes and mechanisms, which may be quantified through

36 interactions with biotic and abiotic elements (Smith et al. 2014). Such interactions often

37 explain species co-occurrence via ecological filtering (Mahecha & Schmidtlein 2008, Drucker

38 et al. 2008, Boaratti & Silva 2015, Menger et al. 2017) or competition (Vitt et al. 2000,

39 Vernes et al. 2005, Santos et al. 2009), and they ultimately may cause speciation even in the

40 absence of conspicuous allopatric forces (DeFaveri et al. 2013). However, few studies have

41 determined the specific contribution of different processes to the organization biological of

42 assemblages. This is mainly due to the lack of spatially explicit data quantifying species

43 occurrence and abundance. Although many taxa appear to be widely distributed along tropical

44 regions, recent studies have shown that their regional distribution may be regionally limited

45 by ecological and historical factors (Dias-Terceiro et al. 2015, Moraes et al. 2016, Alves-

46 Martins et al. 2019).

47 Large Amazonian rivers may play important roles on species diversification, because

48 they interrupt or reduce gene flow (Cracraft 1985, Haffer 1997, Ron 2000). The isolation of

49 organisms on one of the riversides makes interfluvial zones promising areas for endemism,

50 and consequently, opposite riversides represent distinct biogeographic units (Borges & Da

51 Silva 2012, Juen & DeMarco-Jr 2012, Ribas et al. 2012). In addition, evolutionary processes

52 and ecological dynamics acting in isolation between riversides have produced distinct habitats

53 within each side, which may affect organism distribution and density, even in species (or

54 complexes) for which the river does not limit distribution at wide scales (Ortiz et al. 2018).

55 Therefore, interfluvial regions are ideal systems for investigating processes causing non-

56 random species distribution, even in the absence of conspicuous geographical barriers to

57 dispersal and gene flow.

58 Adaptation to local environmental conditions may be driven by a trade-off between

59 availability of vital resources for species, and the ability of species to exploit resources,

60 especially those related to foraging, breeding and thermoregulation (Silva & Araújo 2008).

61 Specifically for Amazonian lizards, high environmental heterogeneity may strongly influence

62 species distribution, because it determines variation in habitat quality along continuous

63 landscapes (Vitt & Carvalho, 1992). Gradients of canopy openness and light incidence

64 (Moraes 2008, Lobão 2008), tree density (Pinto 2006, Bittencourt 2008), leaf-litter depth

65 (Pinto 2006, Bittencourt 2008), prey availability (Lobão 2008, Moraes 2008), clay content in

66 the soil (Pinto 2006), terrain altitude and slope (Pinto 2006, Moraes 2008, Lobão 2008), and

67 distance from waterbodies (Faria et al. 2019) determine the availability of foraging, resting,

68 refuging and thermoregulating sites for distinct species subsets, and therefore structure

69 assemblages through environmental filtering. The relationship between environmental

70 gradients and local lizard assemblage composition may be strong enough that habitat

71 fragmentation changes assemblage composition (Bittencourt 2008).

72 On the other hand, for ectotherms such as lizards, the thermal quality of habitats is

73 essential for the maintenance of metabolic functions that support physiological functions such

74 as growth and embryonic development (Vitt et al. 1997). Therefore, habitat occupancy levels

75 are largely determined by fluctuation in temperature throughout a day or year (Karr &

76 Freemak 1983). In addition, precipitation influences the life history of lizards (Bock et al.

77 2009), in determining food supply (Yom-Tov & Geffen 2006, James & Shine 1988, Brandt &

78 Navas 2011). In fact, the use of climatic variables tends to gain importance in predicting

79 species distribution or investigating ecosystem functionality, especially within the context of

80 global climate change (Guisan et al. 2003, Costa et al. 2008, Rutschmann et al. 2016).

81 Ecosystem functionality is directly associated with local assemblage compositions,

82 and environmental changes reducing functional diversity or increasing levels of functional

83 redundancy imply a reduction in overall ecosystem functions (Naeem 1998). Therefore,

84 functional diversity measures are widely informative regarding assemblage structure and

85 habitat functionality, and consequently useful for decision-making in conservation. The

86 practice of grouping species through functional similarities is not new to community ecology

87 (Polis & Strong 1996). However, the development of the theme has generated methods of

88 measuring functional diversity through mathematical indexes that generate continuous metrics

89 instead of categorical species groups (Petchey & Gaston 2002, 2006). A drawback in

90 quantifying functional diversity based on functional groups is that new categorical levels must

91 be created as traits are added to the model, and one species may belong to more than one

92 group simultaneously. In contrast, one can use numerous functional traits measured as

93 different types of variables (e.g. continuous, binary) to quantify continuous functional

94 diversity, despite choosing how many and which traits are relevant to the study system is

95 often an arbitrary exercise (Petchey & Gaston 2006). Measuring continuous functional

96 diversity may be based on species pairwise dissimilarities in morphological (Resetarits &

97 Chalcraft 2007), physiological, behavioral, and dietary data (Chalcraft & Resetarits 2003,

98 Straub et al. 2010). Although poorly exploited, this approach has revealed important insights

99 into the structure of reptile assemblages (Powney et al. 2010, Rodrigues 2014, Berriozabal-

100 Islas et al. 2017, Fraga et al. 2018), and the role of environmental heterogeneity on limiting

101 functional diversity (Fraga et al. 2018).

102 In the present study we aimed to understand how different environmental gradients

103 influence species richness, composition and functional diversity in heterogeneous rainforests

104 of Amazonia, using lizard assemblage data as a model. We sampled 5 km2 plot systems

105 distributed along 880 km along the interfluvial region between the Purus and Madeira rivers,

106 in southwestern Amazonia. We test the general hypothesis that climatic (temperature and

107 precipitation), edaphic (clay, sand and silt content in the soil) and vegetation-cover (number

108 of trees and basal area) variables cause variation in lizard assemblages along two major

109 phytophysiognomies (open and closed ombrophylous forests) covering the region. We expect

110 that the area covered by the sampling sites contain enough environmental heterogeneity so

111 that sets of species and functional traits co-occurring are not randomly distributed across the

112 landscape.

113

114 METHODS

115

116 STUDY AREA AND SAMPLING DESIGN. — Sampling sites are located along 880 km in

117 the interfluve between the Purus and Madeira rivers, within the Inambari endemism zone

118 (Ribas et al. 2012). The study area covers rainforests crossed by the BR-319 federal highway,

119 which connects Careiro da Várzea to Humaitá, in the state of Amazonas, and rainforests on

120 the west bank of the upper Madeira River, southwestern Amazonian Brazil (Rondônia state).

121 The topography of the region is relatively flat and low (30–60 m above sea level). According

122 to a classification proposed by the Brazilian Institute of Geography and Statistics (IBGE

123 1997), approximately 64.28% (n = 10) of the sampling sites were installed in areas covered by

124 Dense Ombrophylous Forest (DOF), and 35.71% (n = 5) sampling sites are within patches of

125 Open Ombrophylous Forest (OOF). 36

126 There are 15 sampling sites (here after modules) in the study area, but we did not

127 include one of them (M8) in the analyzes. We were not able to fully survey this module

128 during the rainy season, because some of the trails were flooded. The modules were installed

129 according to the RAPELD (Brazilian acronym for rapid survey plus long-term ecological

130 research) method (Magnusson et al. 2005, 2013). Each module is composed of two main 5

131 km-long trails, parallel and separated by 1 km. We sampled 10 modules along the BR-319,

132 and four modules on the west bank of the upper Madeira River (Fig. 1). Each module contains

133 ten 250 m-long plots, 10 m wide in each trail. The plots follow the altitudinal curves to

134 minimize environmental heterogeneity within plots. In this study we used modules as

135 sampling units, because environmental data were not available for all plots.

136 We collected data in August 2010 in the modules on the upper Madeira River, and

137 October to December 2010 in the modules along the BR-319. We found lizards using active

138 visual search (Campbell & Christman 1982) for 60 minutes per plot (average) with two

139 simultaneous observers, 10 m apart. Additionally, we improved sampling cryptic species (e.g.

140 Gymnophthalmidae, Alopoglossidae) by sweeping the leaf litter in a 1 m-wide lane from the

141 central line of the plot.

142 For species that are difficult to identify in the field, we collected a maximum of three

143 specimens. We killed them using a lidocaine-based anesthetic, fixed them in 10%

144 formaldehyde, and stored them in 70% ethanol. We deposited voucher specimens in the

145 collection of Amphibians and Reptiles of the Instituto Nacional de Pesquisas da Amazônia,

146 Manaus, Brazil (INPA-H). Collecting specimens was authorized by a permanent license

147 (RAN-ICMBio/IBAMA nº 13777-2/2008) granted to the expedition coordinator Albertina P.

148 Lima.

149 LIZARD ASSEMBLAGES. —We quantified lizard assemblages using four distinct

150 measures of alpha (species and functional richness) and beta diversity (assemblage

151 composition and dispersion of functional traits). We represented species richness by absolute

152 numbers of taxa per module (including Plica umbra subspecies). We estimated assemblage

153 composition by pairwise Bray-Curtis dissimilarities in taxa abundances. The dissimilarity

154 matrix was summarized by a Principal Coordinate Analysis (PCoA).

155 To quantify lizard assemblages based on functional traits, we used a functional

156 richness index (FRic) and a functional dispersion index (FDis), both implemented in the FD

157 R-package (Laliberté et al. 2014). We selected functional traits that potentially represent

158 interactions among lizards, biotic and abiotic habitat elements. We used morphometric traits

159 because they determine diet composition (e.g. prey type and size) and the use of habitats (Vitt

160 1991, Vitt et al. 1997). We used a digital caliper to measure snout-ventral length, head width,

161 head height, anterior limb length, and posterior limb length. We measured 5–15 individuals

162 per taxa and used average values to estimate functional richness and dispersion. We used

163 foraging mode (active, sedentary ambush, active ambush), because this trait reflects levels of

164 exposure to predators, feed frequency, and consequently defensive behavior and growth rates

165 (Vitt 1991). We used substrate type (terrestrial, arboreal) because this trait represents direct

166 interactions between species and the available habitats (Vitt et al. 2001). We obtained data on

167 foraging mode and substrate in the literature (Ávila-Pires 1995, Vitt et al. 2008).

168 We calculated Gower distances in the functional traits between paired taxa and used a

169 cluster analysis to visualize the dissimilarities among taxa in a dendrogram (Pavoine et al.

170 2009, 2011). We estimated functional richness (FRic) and dispersion (FDis) using the dbFD

171 function of the FD package (Laliberté et al. 2014), based on the sums of the branch lengths of

172 the functional tree (dendrogram) per module. The function returns four different indexes of 38

173 functional alpha and beta diversity, of which we used FRic as a measure of functional alpha

174 diversity, and FDis as a measure of functional beta diversity. Both measures have been

175 described as not biased by number of traits or outliers (Laliberté et al. 2014).

176 ENVIRONMENTAL GRADIENTS. — To estimate the effects of environmental

177 heterogeneity on species richness, assemblage composition, functional richness and

178 dispersion, we used variables that quantify vegetation-cover and soil structure. These

179 variables potentially affect lizard taxonomic and functional diversity measures by determining

180 the availability of foraging, resting, sheltering and thermoregulating sites (Hadden &

181 Westbrooke 1996). Number of trees and clay, sand and silt content in the soil were measured

182 following standard protocols of the Biodiversity Research Program (PPBio), and the methods

183 can be found at http://ppbio.inpa.gov.br/knb/style/skins/ppbio. The basal area of the trees was

184 measured by Schietti et al. (2016).

185 We also tested the influence of climate on each metric of lizard assemblage. We

186 obtained climatic variables from the WorldClim database (Hijmans et al. 2005). The data used

187 in this study comprised interpolated surfaces from mean values of 50 years period (1,950-

188 2,000). To characterize climatic heterogeneity across the study area, we selected all

189 bioclimatic variables available in WorldClim, and we extracted values per centroid

190 geographic coordinates of each module using the DIVA-GIS software (Hijmans et al. 2012).

191 All bioclimatic variables were correlated (Pearson r > 0.6 in all cases). The mean

192 annual rainfall had greatest amplitude (1,930 to 2,624 mm), so we used it as a proxy for the

193 heterogeneity in precipitation along the study area (Table S1). Due to the multicollinearity

194 among the measured climatic variables, it was not possible to use them as independent

195 variables in multiple-parameter regression models. We chose to summarize all the

196 environmental heterogeneity measured using Principal Component Analysis (PCA). The first 39

197 axis of the PCA captured 91.3% of the original variance in the environmental data

198 (precipitation, basal area of the trees and clay content in the soil) and we used it as a

199 biogeographic gradient in the inferential analyzes.

200 To test differences in lizard assemblages between the main forest types sampled (DOF

201 and OOF) we used models of ANOVA, which were constructed with each of the assemblage

202 metrics (species richness, assemblage composition, FRic and FDis) as dependent variables,

203 and forest type as an independent categorical variable. Additionally, we used simple linear

204 regression models to test the influence of the biogeographic gradient summarizing

205 environmental heterogeneity on each of assemblage metrics, separately. To check the

206 consistency of the results, we also used simple linear regression models constructed with

207 assemblage measures as dependent variables, and each of the raw environmental gradients as

208 independent variables. All the models were validated by normally distributed residuals

209 (Shapiro-Wilk P > 0.05 in all cases), not spatially autocorrelated (Moran's I P > 0.05 in all

210 cases). All analyzes were performed in the R computer environment (R Core Team 2019).

211

212 RESULTS

213

214 We found 27 taxa of 17 genera distributed in nine families (Table S2). The

215 Gymnophthalmidae family was the most taxa in the sample, represented by seven taxa.

216 Among the most frequently sampled species are Norops fuscoauratus (85% of the modules, n

217 = 12), Chatogekko amazonicus (78%, n = 11), and Ameiva ameiva (71%, n = 10). Taxa

218 richness varied from 4 to 13 (mean = 8.5) among modules.

219 The first PCoA axis captured 54% of the original dissimilarities among assemblage

220 composition. We found significant differences in the scores produced by the first PCoA axis

221 between forest types (ANOVA F1,12 = 22.44, P = 0.0004). This finding is graphically showed

222 in Fig. 2.

223 The biogeographic gradient summarizing correlated environmental variables explained

224 86% of the variation in assemblage composition (F1,12 = 74.9, P < 0.001, Fig. 3A). This

225 finding suggests that the environmental heterogeneity measured selects different species

226 subsets throughout the study area, which has caused continuous species turnover. The extreme

227 limits of the species turnover gradient are represented by the two sampled forest types (Fig.

228 3A). Although environmental heterogeneity caused species turnover, species richness was

229 randomly distributed along the biogeographic gradient (P < 0.37, Fig. 3B).

230 The simple linear regression models using each individual environmental variable

231 revealed that assemblage composition is primarily characterized by species turnover along the

2 232 gradient of basal area (R = 0.84, F1,12 = 64.12, P < 0.001, residual error = 0.12), precipitation

2 2 233 (R = 0.84, F1,12 = 63.02, P < 0.001, residual error = 0.12), and soil clay content (R = 0.68,

234 F1,12 = 25.70, P < 0.001, residual error = 0.17). Although the environmental heterogeneity of

235 the study area is characterized by two distinct groups of modules that are consistent with the

236 forest types sampled, relationships between assemblage composition and environmental

237 variables can be demonstrated as continuous gradients of species turnover (Fig. 4). None of

238 the measured environmental variables returned significant effects on the richness (P > 0.16 in

239 all cases).

240 The patterns of species turnover caused by precipitation and basal area are

241 demonstrated by absence or low abundance of species at certain regions of the gradients (Fig.

242 5). For instance, nine species were restricted to modules with relatively small basal area (Fig.

243 5A). This result was expected for heliothermic species (e.g. Hoplocercus spinosus), which are

244 tolerant to the higher ultraviolet radiation in open forests. However, some of the species for

245 which distribution was restricted to these modules are not heliothermic (e.g. Iphisa elegans,

246 Dactyloa punctata), which suggests that environmental filtering associated to basal area does

247 not necessarily act on thermoregulation mode. The same species were restricted to modules

248 with relatively low levels of precipitation (Fig. 5B). This finding suggests lizard assemblages

249 structured by interactions between basal area and precipitation, although a larger proportion of

250 species has been widely distributed along the measured precipitation gradient.

251 The clustering by Gower dissimilarities in functional traits among paired species

252 revealed two main groups composed of arboreal and terrestrial species (Fig. 6). The group of

253 terrestrial species was subdivided by foraging mode. We found differences in FRic

254 values between forest types (ANOVA F1,12 = 7.19, P = 0.02). Modules in Dense

255 Ombrophilous Forest had less trait richness. Additionally, FRIc values were not randomly

2 256 distributed along modules (Fig. 7A), but negatively related (R = -0.35, F1,12 = 6.48, P = 0.02,

257 residual error = 9.61) to the biogeographic gradient summarizing environmental

258 heterogeneity. However, these findings were not associated with significant turnover (FDis) in

259 functional diversity (Fig. 7B) between forest types (P = 0.21) or along the biogeographic

260 gradient (P = 0.17).

261 The simple-linear regression models returned FRic (Fig. 8A) values negatively

2 262 affected by basal area (R = -0.39, F1,10 = 7.81, P = 0.01, residual error = 8.81) and

2 263 precipitation (R = -0.43, F1,12 = 9.63, P < 0.001, residual error = 8.93), but not by soil clay

264 content (P = 0.15). The functional turnover rates were relatively low throughout the sampled

265 modules, which caused random variation in FDis values (Fig. 8B) along the gradients of soil

266 clay content (P = 0.29), basal area (P = 0.12) and precipitation (P = 0.40).

267

268 DISCUSSION

269

270 We found that the environmental heterogeneity covered by the Purus-Madeira

271 interfluve predicts spatial structuring of lizard assemblages. This finding is supported by non-

272 random distribution of taxonomic and functional diversity measures across categorical (dense

273 and open Ombrophylous forest) and continuous habitats (biogeographic gradient and

274 individual environmental variables). Interestingly, assemblages defined in the taxonomic

275 dimension were only structured by dissimilarities among paired modules (beta diversity),

276 whereas assemblages defined in the functional dimension were only structured by the

277 absolute-trait richness per module (alpha diversity). These findings suggest that the regional

278 lizard diversity is defined by environmental filtering causing species turnover along the

279 landscape, and selection of functional trait subsets that are nested within the global trait

280 diversity. Although large Amazonian rivers are commonly reported as vicariant barriers

281 promoting biodiversity in Amazonia (Haffer 1997, Simões et al. 2008, Antonelli et al. 2010,

282 Ribas et al. 2012, Smith et al. 2014, Boubli et al. 2015), we showed the relevance of

283 environmental gradients as predictors of multi-taxa organism distribution, even in the absence

284 of conspicuous vicariance. Our results also support the importance of investigating a same

285 assemblage dataset under different dimensions of biodiversity for ecology and conservation

286 (see Fraga et al. 2018).

287 Although most of the species sampled in this study are widely distributed across

288 Amazonia or even different ecosystems in South America (Ávila-Pires 1995, Vitt et al. 2008,

289 Ribeiro-Júnior 2016), they were regionally restricted to optimal habitat types or fractions of

290 environmental gradients. Lizard species turnover along environmental gradients has been 43

291 demonstrated in different regions of the Amazon, specially related to distance from water

292 courses (Pinto 2006, Moraes et al. 2016, Faria et al. 2019). However, the ecological models

293 tested in such studies were usually set up to quantify environmental heterogeneity by multiple

294 independent variables. Such an approach assumes certain levels of covariance among multiple

295 environmental variables, which may be useful to control for the effects of covariates on the

296 estimated assemblage composition. Here we demonstrated that patterns of lizard spatial

297 structure may also be captured by reducing multivariate environmental heterogeneity in a

298 single independent variable (biogeographic gradient represented by the first axis of a PCA).

299 Despite the slight loss of information due to the forced dimensionality reduction, our findings

300 suggest that species-habitat associations based on multiple environmental variables may be

301 detected even by models that do not assume covariance.

302 By testing simple linear regression models, we found species turnover along a gradient

303 of soil clay content. This is assumed as an indirect effect, because soil texture affects

304 invertebrate prey density and water retention (Woinarski et al. 1999, Menger et al. 2017). In

305 the Amazon, soils with higher clay content have been associated with shallower groundwater

306 (Schietti et al.2014), which may contribute to the pattern of co-occurrence of the species

307 locally. Additionally, we found species turnover along basal area gradients and precipitation.

308 The vegetation structure for the lizards is directly responsible for the supply of microhabitats

309 and availability of food, besides acting for the regulation of the air temperature, and affecting

310 the direct solar incidence in the forests (Silva & Araújo 2008), able to influence demographic

311 patterns in assemblages. These thermo-regulatory requirements are important for the

312 physiological processes in tropical lizards, because they maintain several biological aspects of

313 the species (Huey & Slatkin, 1976, Bergallo & Rocha, 1993, Ortega & Pérez-Mellado 2016,

314 Pontes et al. 2018). Precipitation, however, is almost never approached in the studies of the

315 spatial structure of assemblages of Amazonian lizards (Vitt 1991, Pinto 1999), but it is also an

316 important factor for the climatic conditions of the environment, necessary for

317 thermoregulation of the species, apart from contributing to the food niche, by influencing the

318 increase of essential invertebrates for the diet of several species (Woinarski et al. 1999,

319 Rutschmann et al. 2016).

320 We found significant effects of the biogeographic gradient measured on the functional

321 trait richness. This finding was supported by negative relationships between FRic with basal

322 area and precipitation, although they were not associated with trait turnover along the study

323 area. These findings suggest that dense and very rainy forests contain functionally

324 homogeneous lizard assemblages. Relatively low trait richness suggesting regional filtering of

325 redundant functional traits. In contrast, relatively open and less rainy forests had higher trait

326 richness, is usually associated with minor effects of competition, through competitive

327 exclusion, since the available habitats allow the establishment of functionally redundant

328 species (Petchey et al. 2007, Straub et al. 2010). The influence of such processes changes

329 across environmental gradients, where the environmental filtering will exert more influence in

330 more stressful environmental. Future studies should focus on the explicit effects of an

331 interaction between environmental conditions and competition on the regional distribution of

332 functional traits.

333 Functional traits reflect environmental requirements and tolerances and are responsible

334 for directly influencing the success of foraging, escape ability, predation, and reproductive

335 aspects of the species (Dobson & Michener, 1995, Chown et al. 2004). Comparative studies

336 among body, behavioral and habitat characteristics have been reported for a long time in the

337 literature (Vitt et al. 1997, Caldwell & Vitt 1999). In our study, rainfall gradients and basal area

338 were efficient environmental filters to predict changes in the species' functional richness. 45

339 Open Ombrophylous forest environments have lower forest densities and rainfall averages,

340 and tend to select larger numbers of heliothermic, terrestrial species with larger hind limbs

341 capable of improving race performance in more exposed habitats (Silva & Araújo 2008).

342 Differently, more densely forested environments, with high annual precipitation, or subject to

343 periodic flooding, result in forests with denser and stratified canopy, and provide more stable

344 microenvironment for the arboreal or non-heliothermic species (Magnuson & Silva 1993).

345 Body size and shape are also characteristics that determine the permanence of the species in

346 the different habitats (Rickefs & Travis 1980): thinner and longer bodies (e.g., Anolis lizards)

347 are associated with the finer branches, whereas for trees with larger trunks the bodies are

348 more robust and flattened (e.g., Plica lizards) (Vitt et al. 2008).

349 Habitat disturbance is one important anthropogenic factor that influence ecosystems

350 resulting in changes in environmental structure and biotic composition (Hobbs et al. 2009),

351 mainly in tropical forests that harbor an exceptionally high diversity. The Amazon has been

352 suffering from these anthropic impacts, whether through fragmentation, deforestation or

353 changes in land use and land cover (Val & Marcovitch 2019), which tends to the imminent

354 loss of species. Although habitat conservation is an important factor, knowledge of species

355 distribution and coexistence is essential for conservation mitigation measures (Roll et al.

356 2017, Magnuson et al. 2016). For the Amazonian lizards the high phenotypic conservatism,

357 intraspecific polymorphism, and low detection probabilities, hinders the true limits of

358 occurrence of the species (Fouquet et al. 2015, Ribeiro-Júnior & Amaral 2016). For the

359 Purus-Madeira Interfluve different structural aspects of the environment define the

360 heterogeneity of habitats (Ximenes, 2008). This scenario consists of an opportunity to

361 understand the patterns of distribution of lizards and the relation of these patterns to the life

362 history traits of each species, since for environmental characteristics it has a strong influence

363 in limiting the distribution in this group (Costa et al. 2008), especially when we associate

364 diverse measures of diversity, capable of measuring the maintenance of ecosystem processes

365 that operate in long periods (Devictor et al. 2010, Fraga et al. 2018).

366 In summary, our study was pioneer in evaluate the wide-scale environmental effects

367 on Amazonian lizard assemblages and identify that the structural complexity along a

368 biogeographic gradient have a significant impact on the composition and richness of

369 functional characteristics of lizards. Environmental filters related to edaphic, vegetation and

370 rainfall gradients along the region of the Purus-Madeira influence the species turnover, and

371 determine the differences found between assemblages in the open and dense ombrophilous

372 forests. Finally, this study reinforces the relevance of the studied area for species conservation

373 and management. Future studies on this scale might elucidate patterns of coexistence and

374 distribution of species of Amazonian organisms and their associations to the environment

375 along continuous forests.

376

377 Acknowledgments

378 This study was funded by the Brazilian Conselho Nacional de Desenvolvimento

379 Científico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado do Amazonas

380 (FAPEAM) under grants conceded to A.P.L. (CNPq: Programa Ciência sem Fronteiras process

381 401327/2012- 4; FAPEAM/CNPq: PRONEX process 445653/2009), FAPEAM/CNPq:

382 PRONEX process 1600/2006) to W. E. Magnusson, PPBio—Programa de Pesquisas em

383 Biodiversidade (CNPq 558318/2009-6) and Programa de Conservação da Vida Selvagem da

384 Santo Antônio Energia S.A. Conselho Nacional de Desenvolvimento Científico e Tecnológico

385 (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) granted

386 PhD scholarships to GMP. CAPES provided a PNPD postdoc grant to RF and CNPq provided 47

387 productivity grants to ILK and APL. We collected data under RAN-ICMBio / IBAMA permit

388 # 13777-2.

389

390 Literature cited

391 ALVES-MARTINS, F., L. S. BRASIL, L. JUEN, P. DE MARCO-JR, J. STROPP, AND J.

392 HORTAL. 2019. Metacommunity patterns of Amazonian Odonata: the role of environmental

393 gradients and major rivers. Peer J, 7: e6472.

394 ANTONELLI, A., A. QUIJADA-MASCAREÑAS, A. J. CRAWFORD, J. M. BATES, P. M.

395 VELAZCO, AND W. WÜSTER. 2010. Molecular studies and phylogeography of Amazonian

396 tetrapods and their relation to geological and climatic models. In: C. Hoorn and F. P.

397 Wesselingh (Eds.), Amazonia, landscape and species evolution, pp. 386–403. Blackwell

398 Publishing, Oxford, UK.

399 ÁVILA-PIRES, T. C. S. 1995. Lizards of Brazilian Amazonia (Reptilia: Squamata).

400 Leiden, Netherlands: Zoologische Verhandeligen.706p.

401 BERRIOZABAL-ISLAS, C., L. M. BADILLO-SALDAÑA, A. RAMÍREZ-BAUTISTA, AND C.

402 E. MORENO. 2017. Effects of habitat disturbance on lizard functional diversity in a tropical

403 dry forest of the Pacific Coast of Mexico. Trop Conserv Sci. 10: 1–11.

404 BERGALLO, H. G. AND C. F. D. ROCHA. 1993. Activity pattern and body temperature of

405 two sympatric lizards with different foraging tactics in southeastern Brazil. Amphibia Reptilia.

406 4: 312–315.

407 BITTENCOURT, S. 2008. Insularização como agente de fragmentação florestal em

408 comunidades de lagartos da Amazônia Central. MSc Dissertation. Instituto Nacional de Pesquisas

409 da Amazônia, Manaus. Available in: https://bdtd.inpa.gov.br/handle/tede/1846.

410 BOARATTI, A. Z., AND F. R. DA SILVA. 2015. Relationships between environmental

411 gradients and geographic variation in the intraspecific body size of three species of frogs

412 (Anura). Austral ecology. 40: 869–876.

413 BOCK, B. C., A. M. ORTEGA, A. M. ZAPATA, AND V. P. PÁEZ. 2009. Microgeographic

414 body size variation in a high elevation Andean anole (Anolis mariarum; Squamata,

415 Polychrotidae). Revista de biología tropical, 57: 1253–1262.

416 BORGES, S. H., AND J. M. DA-SILVA. 2012. A new area of endemism for Amazonian

417 birds in the Rio Negro Basin. The Wilson Journal of Ornithology. 124: 15–23.

418 BOUBLI, J.P., C. RIBAS, J. W. L. ALFARO. 2015. Spatial and temporal patterns of

419 diversification on the Amazon: A test of the riverine hypothesis for all diurnal primates of

420 Rio Negro and Rio Branco in Brazil. Mol Phylogenet Evol. 82: 400–412. DOI:

421 10.1016/j.ympev.2014.09.005.

422 BRANDT, R., AND C. A. NAVAS. 2011. Life-history evolution on Tropiduridae lizards:

423 influence of lineage, body size and climate. PLoS ONE. 6: e20040. Doi:

424 10.1371/journal.pone.0020040.

425 CALDWELL, J. P., AND L. J. VITT. 1999. Dietary asymmetry in leaf litter frogs and

426 lizards in a transitional northern Amazonian rain forest. Oikos. 84: 383–397.

427 CAMPBELL, H. W. AND S. P. CHRISTMAN. 1982. Field techniques for herpetofaunal

428 community analysis. In: N. J. Scott (Ed.). Herpetological Communities: A Symposium of the

429 Society for the Study of Amphibians and Reptiles and the Herpetologist’s League, pp. 193–

430 200. U.S. Dept. of Interior, Fish and Wildlife Service - Wildlife Research Report,

431 Washington, USA.

432 CHALCRAFT, D. R., AND J. R. RESETARITS. 2003. Mapping functional similarity of

433 predators on the basis of trait similarities. The American Naturalist, 162: 390–402.

434 CHOWN, S.L., K. J. GASTON, AND D. H. ROBINSON. 2004. Macrophysiology: large–scale patterns

435 in physiological traits and the ecological implications. Functional Ecology. 18: 159–167.

436 COSTA, G. C., L. J. VITT, E. R. PIANKA, D. O. MESQUITA, AND G. R. COLLI. 2008.

437 Optimal foraging constrains macroecological patterns: body size and dietary niche breadth

438 in lizards. Global Ecology and Biogeography, 17: 670-677. DOI: 10.1111/j.1466-

439 8238.2008.00405.x.

440 CRACRAFT, J. 1985. Historical biogeography and patterns of differentiation within the

441 South American avifauna: areas of endemisms. Ornithological Monographs. 36: 49–84.

442 DEFAVERI, J., P. R. JONSSON, AND J. MERILÄ. 2013. Heterogeneous genomic

443 differentiation in marine threespine sticklebacks: adaptation along an environmental

444 gradient. Evolution, 67: 2530–2546.

445 DIAS-TERCEIRO, R. G., I. L. KAEFER, R. FRAGA, M. C. ARAÚJO, P. I. SIMÕES, A. P.

446 LIMA. 2015. A matter of scale: historical and environmental factors structure anuran

447 assemblages from the upper Madeira River, Amazonia. Biotropica. 47: 259–266. DOI:

448 10.1111/btp.12197.

449 DOBSON, F. S., AND G. R. MICHENER. 1995. Maternal traits and reproduction in

450 Richardson's ground squirrels. Ecology. 76: 851–862.

451 FARIA, A. S., M. MENIN, I. L. KAEFER. 2019. Riparian zone as a main determinant of

452 the structure of lizard assemblages in upland Amazonian forests. Austral Ecol. 1: 1–9.

453 DOI: 10.1111/aec.12754.

454 FOUQUET, A, E. A. COURTOIS, D. BAUDAIN, J. D. LIMA, S. M. SOUZA, B. P. NOONAN,

455 AND M. T. RODRIGUES. 2015. The trans-riverine genetic structure of 28 Amazonian frog

456 species is dependent on life history. J Trop Ecol. 31: 361–373. DOI:

457 10.1017/S0266467415000206

458 FRAGA, R., M. FERRÃO, A. J. STOW, W. E. MAGNUSSON, A. P. LIMA. 2018. Different

459 environmental gradients affect different measures of snake β-diversity in the Amazon

460 rainforests. PeerJ. 6: e5628. DOI: 10.7717/peerj.5628

461 POLIS, G. A. AND D. R. STRONG. 1996. Food Web Complexity and Community

462 Dynamics. The American Naturalist. 147: 813–846.

463 GUISAN, A., AND U. HOFER. 2003. Predicting reptile distributions at the mesoscale:

464 relation to climate and topography. J Biogeogr. 30: 1233–1243.

465 HADDEN, S. A., AND M. E. WESTBROOKE. 1996. Habitat relationships of the

466 herpetofauna of remnant buloke woodlands of the Wimmera Plains, Victoria. Wildlife

467 Research. 23: 363–372. DOI: 10.1071/WR9960363

468 HAFFER, J. R. 1997. Alternative models of vertebrate speciation in Amazonia: an

469 overview. Biodiversity & Conservation. 6: 451–476.

470 HUEY, R.B. AND M. SLATKIN. 1976. Costs and benefits of lizard thermoregulation.

471 Quarterly Review of Biology. 51: 363–384.

472 HIJMANS, R. J., S. E. CAMERON, J. L. PARRA, P. G. JONES, AND A. JARVIS. 2005. Very

473 high resolution interpolated climate surfaces for global land areas. International Journal of

474 Climatology. 25: 1965–1978. DOI: 10.1002/joc.1276

475 HOBBS, R. J., E. HIGGS AND J. A. HARRIS. 2009. Novel ecosystems: implications for

476 conservation and restoration. Trends in ecology & evolution, 24: 599–605. DOI:

477 10.1016/j.tree.2009.05.012

478 IBGE. 1997. Instituto Brasileiro de Geografia e Estatística. Recursos naturais e meio

479 ambiente: uma visão do Brasil. Rio de Janeiro: IBGE. Available in:

480 http://biblioteca.ibge.gov.br/biblioteca-catalogo.html?id=27704&view=detalhes.

481 JAMES, C., AND R. SHINE. 1988. Life-history strategies of Australian lizards: a

482 comparison between the tropics and the temperate zone. Oecologia. 75: 307–316.

483 JUEN, L., AND P. DE-MARCO. 2012. Dragonfly endemism in the Brazilian Amazon:

484 competing hypotheses for biogeographical patterns. Biodiversity and Conservation. 21:

485 3507–3521.

486 KARR, J. R., AND K. E. FREEMARK. 1983. Habitat selection and environmental

487 gradients: dynamics in the "stable" tropics. Ecology. 64: 1481–1494.

488 LALIBERTÉ, E., P. LEGENDRE, B. SHIPLEY, AND M. E. LALIBERTÉ. 2014. Package

489 ‘FD’. Measuring functional diversity from multiple traits, and other tools for functional

490 ecology. Available in: https://mran.microsoft.com/snapshot/2014-11-

491 17/web/packages/FD/FD.pdf.

492 LOBÃO, P. S. P. 2008. Associações no uso do habitat por cinco espécies de lagartos

493 amazônicos. MSc Dissertation. Instituto Nacional de Pesquisas da Amazônia, Manaus.

494 MAGNUSSON, W. E., A. P. LIMA, R. LUIZÃO, F. LUIZÃO, F. R. C. COSTA, C. V.

495 CASTILHO, AND V. F. KINUPP. 2005. RAPELD: a modification of the Gentry method for

496 biodiversity surveys in long-term ecological research sites. Biota Neotropica. 5: 1–6.

497 MAGNUSSON, W. E., R. B. N. PEZZINI, F. F. BACCARO, F. BERGALLO, H. PENHA, J.

498 RODRIGUES, D. J. VERDADE, L. L. MARTINS, A. ALBERNAZ, A. L. HERO, J. M. LAWSON, B. E.

499 CASTILHO, C. DRUCKER, D. FRANKLIN, E. MENDONÇA, F. COSTA, F. GALDINO, G. GUYER, C.

500 ZUANON, J. VALE, J. SANTOS, J. L. C. LUIZÃO, R. C. CINTRA, R. I. BARBOSA, R. LISBOA; A.

501 KOBLITZ, R. V. CUNHA, C. N. PONTES, AND A. R. MENDES. 2013. Biodiversidade e

502 Monitoramento Ambiental Integrado: o sistema RAPELD na Amazônia. 1ª ed. Santo André -

503 SP: Publisher Attema. 335p.

504 MAHECHA, M. D., AND S. SCHMIDTLEIN. 2008. Revealing biogeographical patterns by

505 nonlinear ordinations and derived anisotropic spatial filters. Global Ecology and

506 Biogeography. 17: 284–296.

507 MENGER, J., W. E. MAGNUSSON, M. J. ANDERSON, M. SCHLEGE, G. PE'ER, K. HENLE.

508 2017. Environmental characteristics drive variation in Amazonian understorey bird

509 assemblages. PLoS ONE. 2: e0171540. Doi: 10.1371/journal.pone.0171540.

510 MORAES, L. F. P. 2008. Diversidade beta em comunidades de lagartos em duas

511 Ecorregiões distintas na Amazônia. MSc Dissertation. Instituto Nacional de Pesquisas da

512 Amazônia, Manaus. Available in: https://bdtd.inpa.gov.br/handle/tede/736.

513 MORAES, L. J., D. PAVAN, M. C. BARROS, C. C. RIBAS. 2016. The combined influence

514 of riverine barriers and flooding gradients on biogeographical patterns for amphibians and

515 squamates in south‐eastern Amazonia. J Biogeogr. 43: 2113–2124. Doi:

516 10.1111/jbi.12756.

517 NAEEM, S. 1998. Species redundancy and ecosystem reliability. Conserv. Biol. 12:

518 39–45.

519 ORTEGA, Z. AND V. PÉREZ-MELLADO. 2016. Seasonal patterns of body temperature

520 and microhabitat selection in a lacertid lizard. Acta Oecologica. 77: 201e206

521 ORTIZ, D. A., A. P. LIMA, F. P. WERNECK. 2018. Environmental transition zone and

522 rivers shape intraspecific population structure and genetic diversity of an Amazonian rain

523 forest tree frog. Evolutionary Ecology. 32: 359–378.

524 PAVOINE, S., E. VELA, S. GACHET, G. BE LAIR, AND M. B. BONSALL, 2011. Linking patterns

525 in phylogeny, traits, abiotic variables and space: a novel approach to linking environmental

526 filtering and plant community assembly. Journal of Ecology. 99: 165–175.

527 PAVOINE, S., J. VALLET, A. B. DUFOUR, S. GACHET, AND H. DANIEL. 2009. On the

528 challenge of treating various types of variables: application for improving the measurement

529 of functional diversity. Oikos. 118: 391–402. DOI: 10.1111/j.1600-0706.2008.16668.x

530 PETCHEY, O. L., GASTON, K. J. 2002. Functional Diversity (FD), species richness, and

531 community. Ecology Letters. 5: 402–411.

532 PETCHEY, O. L., GASTON, K. L. 2006. Functional diversity: back to basics and looking

533 forward. Ecology Letters. 9: 741–758. DOI: 10.1111/j.1461-0248.2006.00924.x.

534 PETCHEY, O. L., K. L. EVANS, I. S. FISHBURN, AND K. J. GASTON. 2007. Low

535 functional diversity and no redundancy in British avian assemblages. J. Anim. Ecol. 76:

536 977–988.

537 PINTO, M. G. M. 2006. Diversidade Beta, métodos de amostragem e influência de

538 fatores ambientais sobre uma comunidade de lagartos na Amazônia Central. PhD

539 Dissertation. Instituto Nacional de Pesquisas da Amazônia, Manaus.

540 PONTES-DA-SILVA, E., W. E. MAGNUSSON, B. SINERVO, G. H. CAETANO, D. B MILES,

541 G. R. COLLI, AND F. P. WERNECK. 2018. Extinction risks forced by climatic change and

542 intraspecific variation in the thermal physiology of a tropical lizard. J therm biol. 73: 50–

543 60. DOI: 10.1016/j.jtherbio.2018.01.013.

544 POWNEY, G. D., R. GRENYER, C. D. L. ORME, I. P. F. OWENS, AND S. MEIRI. 2010.

545 Hot, dry and different: Australian lizard richness is unlike that of mammals, amphibians

546 and birds. Global Ecology and Biogeography. 19: 386–396.

547 R DEVELOPMENT CORE TEAM. 2019. A language and environment for statistical

548 computing. Vienna, Austria: R Foundation for Statistical Computing. Available in:

549 https://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf. cited 2 March 2019.

550 RESETARITS, W. J., AND D. R. CHALCRAFT. 2007. Functional diversity within a

551 morphologically conservative genus of predators: implications for functional equivalence

552 and redundancy in ecological communities. Functional Ecology. 21: 793–804. DOI:

553 10.1111/j.1365-2435.2007.01282.x

554 RIBAS, C.C., A. ALEIXO, A. C. R. NOGUEIRA, C. Y. MIYAKI, J. CRACRAFT. 2012. A

555 palaeobiogeographic model for biotic diversification within Amazonia over the past three

556 million years. Proc Bio Sci. 279: 681–689. DOI: 10.1098/rspb.2011.1120.

557 RIBEIRO-JÚNIOR, M.A., AND S. AMARAL. 2016. Diversity, distribution, and

558 conservation of lizards (Reptilia: Squamata) in the Brazilian Amazonia. Neotropical

559 Biodiversity. 2: 195–421.

560 RODRIGUES, G. B. F. 2014. Padrões de diversidade (riqueza, filogenética e funcional)

561 de quelônios continentais da América do Sul, seus processos geradores e suas

562 consequências para a conservação. MSc Dissertation. Universidade de Brasília, Brasília.

563 ROLL, U., A. FELDMAN, M. NOVOSOLOVA, A. ALLISON, A. M. BAUER, R. BERNARD,

564 AND G. R. COLLI. 2017. The global distribution of tetrapods reveals a need for targeted

565 reptile conservation. Nature Ecology & Evolution, 1: 1677–1682. DOI: 10.1038_s41559-

566 017-0332-2.

567 RON, S. R. 2000. Biogeographic area relationships of lowland Neotropical rainforest

568 based on raw distributions of vertebrate groups. Biol J Linn Soc Lond, 71: 379–402. DOI:

569 10.1006/bijl.2000.0446.

570

571 RUTSCHMANN, A., D. B. MILES, J. F. LE-GALLIARD, M. RICHARD, S. MOULHERAT,

572 B. SINERVO, AND J. CLOBERT. 2016. Climate and habitat interact to shape the thermal

573 reaction norms of breeding phenology across lizard populations. J Anim Ecol. 85: 457–

574 466.

575 SANTOS, E. S., R. MAIA, AND R. H. MACEDO. 2009. Condition-dependent resource

576 value affects male–male competition in the blue–black grassquit. Behavioral Ecology. 20:

577 553–559.

578 SCHIETTI, J., T. EMILIO, C. D. RENNÓ, D. P. DRUCKER, F. R. COSTA, AND A. NOGUEIRA.

579 2014. Vertical distance from drainage drives floristic composition changes in an Amazonian

580 rainforest. Plant Ecology & Diversity. 7: 241–253.

581 SCHIETTI, J., D. MARTINS, T. EMILIO, P.F. SOUZA, C. LEVIS, AND F.B. BACCARO.

582 2016. Forest structure along a 600 km transect of natural disturbances and seasonality

583 gradients in central-southern Amazonia. J Ecol. 104: 1335–1346. DOI: 10.1111/1365-

584 2745.12596.

585 SILVA, V. DE N., A. F. B. ARAÚJO. 2008. Ecologia dos lagartos brasileiros. 1ª ed. Rio

586 de Janeiro, Brazil: Technical Books Editora. 271p.

587 SIMÕES, P. I., A. P. LIMA, AND W. E. MAGNUSSON. 2008. Acoustic and morphological

588 differentiation in the frog Allobates femoralis: Relationships with the upper Madeira river

589 and other potential geological barriers. Biotropica. 40: 607–614. DOI: 10.1111/j.1744-

590 7429.2008.00416.x.

591 SMITH, A. L., C. M. BULL, M. G. GARDNER, D. A. DRISCOLL. 2014. Life history

592 influences how fire affects genetic diversity in two lizard species. Mol Ecol. 23: 2428–

593 2441. DOI: 10.1111/mec.12757.

594 STRAUß, A., E. REEVE, R-D. RANDRIANIAINA, M. VENCES, AND J. GLOS. 2010. The

595 world’s richest tadpole communities show functional redudancy and low functional

596 diversity: ecological data on madagascar’s stream-dwelling amphibian larvae. Ecology. 1:

597 10–12.

598 VERNES, K., L. C. POPE, C. J. HILL, AND F. BÄRLOCHER. 2005. Seasonality, dung

599 specificity and competition in dung beetle assemblages in the Australian Wet Tropics, north-

600 eastern Australia. J Trop Ecol. 21: 1–8.

601 VITT, L. J. 1991. Ecology and life history of the wide-foraging lizard Kentropyx

602 calcarata (Teiidae) in Amazonian Brazil. C J Zoo. 69: 2791–2799.

603 VITT, L. J., AND C. M. D. CARVALHO. 1992. Life in the trees: the ecology and life

604 history of Kentropyx striatus (Teiidae) in the Lavrado area of Roraima, Brazil, with

605 comments on the life histories of tropical teiid lizards. Can J Zool. 70: 1995–2006. DOI:

606 10.1139/z92-270.

607 VITT, L. J., P. A. ZANI, A. P. LIMA. 1997. Heliotherms in tropical rain forest: the ecology

608 of Kentropyx calcarata (Teiidae) and Mabuya nigropunctata (Scincidae) in the Curuá-Una of

609 Brazil. J Trop Ecol. 13: 199–220. DOI: 10.1017/S0266467400010415.

610 VITT, L. J., S. S. SARTORIUS, T. C. S. ÁVILA-PIRES, M. C. ESPOSITO, AND D. B. MILES.

611 2000. Niche segregation among sympatric Amazonian teiid lizards. Oecologia. 122: 410–420.

612 VITT, L. J., S. S. SARTORIUS, T. C. S. ÁVILA-PIRES, AND M. C. ESPÓSITO. 2001. Life

613 on the leaf litter: the ecology of Anolis nitens tandai in the Brazilian Amazon. Copeia. 2:

614 401–412.

615 VITT, L. J., W. E. MAGNUSSON, T. C. S. ÁVILA-PIRES, A. P. LIMA. 2008. Guia de Lagartos

616 da Reserva Adolpho Ducke, Amazônia Central. 1ª ed. Manaus- Brazil: Áttema Design

617 Editorial.180p.

618 WIENS, J. J., R. A. PYRON, AND D. S. MOEN. 2011. Phylogenetic origins of local‐scale

619 diversity patterns and the causes of Amazonian megadiversity. Ecol let. 14: 643–652.

620 WOINARSKI, J. C. Z., A. FISHER, AND D. MILNE. 1999. Distribution patterns of vertebrates

621 in relation to an extensive rainfall gradient and variation in soil texture in the tropical savannas

622 of the Northern Territory, Australia. J trop Ecol. 15: 381–398.

623 XIMENES, A. C. 2008. Mapas auto-organizáveis para a identificação de ecorregiões no

624 interflúvio Madeira-Purus: uma abordagem da biogeografia ecológica. PhD Dissertation.

625 Instituto Nacional de Pesquisas Espaciais, São José dos Campos.

626 YOM-TOV, Y. AND E. GEFFEN. 2006. Geographic variation in body size: the effects of

627 ambient temperature and precipitation. Oecologia. 148: 213–218.

628

629

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631

632

633

634

635

636

637

638

639

640

641 58

642 Tables

643 Table S1 Environmental variables used as proxy for the wide-scale biogeographic 644 gradient. Minimum and maximum values for each site along the Purus-Madeira interfluve.

645

646 Annual Sampling Soil clay Tree basal 647 Precipitation Modules contente (μm) área (m2/há) (mm) 648 M-1 11.5 – 29.3 19.9 – 25.32 2156 649 M-2 13.25 – 21.25 25.41 – 33.12 2170 650 M-3 18.45 – 31.5 22.0 – 31.97 2272 651 M-4 12.31 – 30.23 28.6– 36.84 2410 652

653 M-5 10.5 – 14.5 27.95 – 38.9 2609

654 M-6 39.06 – 47.74 29.71 – 34.86 2624

655 M-7 13.5 – 28.7 30.93 – 35.83 2589

656 M-9 19 – 26 30.88 – 32.77 2556 657 M-10 11.75 – 14 27.8 – 32.53 2437 658 M-11 12.5 – 22.75 24.65 – 30.63 2270 659 M-12 62.2 – 70.4 10.34 – 17.46 2067.25 660 661 M-13 59.2 – 72.3 12.44 – 26.72 2004

662 M-14 49.2 – 54 13.5 – 20.47 1970

663 M-15 50.55 –68.89 13.8 – 27.1 1930

664

665

666

667

668 Table S2 List of lizard taxa found along the Purus-Madeira Interfluve. OOF= Open

669 Ombrophilous Forest, and DOF= Dense Ombrophilous Forest.

Family/Taxa DOF OOF

ALOPOGLOSSIDAE

Alopoglossus angulatus (Linnaeus, 1758) - +

Alopoglossus atriventris (Duellman, 1973) + -

DACTYLOIDAE

Norops fuscoauratus D'Orbigny, 1837 + +

Norops ortonii Cope, 1868 + +

Dactyloa punctatus Daudin, 1802 + +

Norops tandai Ávila-Pires, 1995 + -

Dactyloa transversalis Duméril, 1851 + +

GYMNOPHTHALMIDAE

Arthrosaura reticulata (O'Shaughnessy, 1881) + -

Cercosaura argula (Peters, 1863) + +

Cercosaura ocellata (Wagler, 1830) - +

Iphisa elegans (Gray, 1851) - +

Loxopholis osvaldoi Ávila-Pires, 1995 + -

Loxopholis percarinatum Müller, 1923 + -

Tretioscincus agilis (Ruthven, 1916) - +

HOPLOCERCIDAE

Hoplocercus spinosus (Fitzinger, 1843) - +

PHYLLODACTYLIDAE

Thecadactylus solimoensis Bergmann and Russell, 2007 - +

SCINCIDAE

Copeoglossum nigropunctatum (Spix, 1825) + +

Varzea bistriata (Spix, 1825) + -

SPHAERODACTYLIDAE

Chatogekko amazonicus (Andersson, 1918) + +

Gonatodes hasemani (Griffin, 1917) - +

Gonatodes humeralis (Guichenot, 1855) + +

TEIIDAE

Ameiva ameiva (Linnaeus, 1758) + +

Kentropyx altamazonica (Cope, 1876) + +

Kentropyx pelviceps (Cope, 1868) + +

TROPIDURIDAE

Plica umbra ochrocollaris (Linnaeus, 1758) + +

Plica umbra umbra (Linnaeus, 1758) + -

Uranoscodon superciliosus (Linnaeus,1758) + +

670

671

672

673

674

675

676

677

678 Figure legends

679

680 FIGURE 1. Sampling RAPELD modules along the BR-319 federal highway (M1–M11) and

681 the upper Madeira River (M12–M15). The module M8 (in red) was not sampled because it

682 was flooded during the rainy season. Different colors show patches of natural or

683 anthropogenic landscapes, as detailed in the inset legend.

684

685 FIGURE 2. Lizard assemblage composition based on abundance data from 14 sampling

686 modules installed in the Purus-Madeira interfluve, southwestern Amazonian Brazil.

687 Assemblage composition was summarized by the first two axes of a Principal Coordinates

688 Analysis (PCoA) applied on a Bray-Curtis pairwise dissimilarities matrix. Note the

689 segregation in assemblage composition between Open Ombrophilous Forest (light blue

690 circles), and Dense Ombrophilous Forest (dark blue circles).

691

692 FIGURE 3. Relationship between the biogeographic gradient summarizing environmental

693 variables as a PCA axis and lizard assemblage composition (A) and taxa richness (B) sampled

694 in 14 modules along the Purus-Madeira intefluve, southwestern Amazonian Brazil. Light blue

695 circles = Open Ombrophilous Forest; dark blue circles = Dense Ombrophilous Forest.

696

697 FIGURE 4. Relationship between environmental variables and lizard assemblage composition

698 summarized by the first axis of a PCoA applied on Bray-Curtis dissimilarities among paired

699 sampling modules along the Purus-Madeira interfluve, Amazonia. Light blue circles = Open

700 Ombrophilous Forest; dark blue circles = Dense Ombrophilous Forest.

701

702 FIGURE 5. Ordination of 5 km2 sampling modules along gradients of tree basal area (A) and

703 annual precipitation (B) in southwertern Amazonia. The height of the rectangles denotes

704 abundance of lizard individuals per taxon.

705

706 FIGURE 6. Clustering of Gower dissimilarities in functional traits of lizards sampled in 14

707 modules along the Purus-Madeira interfluve, southwestern Amazonia. The blue circle

708 represents the first division of terrestrial and arboreal species. The circle in red shows a

709 second division for the terrestrial species between the species of active foragers and ambush.

710

711 FIGURE 7. Relationships between lizard (A) functional richness (FRic) and (B) functional

712 dispersion (FDis) with a biogeographic gradient summarizing climatic and vegetation cover

713 variables in a PCA axis. Light blue circles = Open Ombrophilous Forest; dark blue circles =

714 Dense Ombrophilous Forest.

715

716 FIGURE 8. Relationships between lizard functional richness (FRic) and functional dispersion

717 (FDis) and environmental gradients measured in 14 sampling modules along the Purus-

718 Madeira interfluve, southwestern Amazonia. Light blue circles = Open Ombrophilous Forest,

719 dark blue circles = Dense Ombrophilous Forest.

720

721

722

723

724 63

Figures

Capítulo 3

Gabriela Marques Peixoto; Rafael de Fraga; Maria C. Araújo; Igor Luis Kaefer; Albertina Pimentel Lima. Hierarchical effects of historical and environmental factors on lizard assemblages in the upper Madeira river, Amazonian Brazil. Manuscrito submetido para a PloS One.

1 Hierarchical effects of historical and environmental factors on 2 lizard assemblages in the upper Madeira river, Amazonian 3 Brazil

6 Gabriela Marques Peixoto1*¶, Rafael de Fraga2¶, Maria C. Araújo1¶, Igor Luis Kaefer1,3¶,

7 Albertina Pimentel Lima1¶

11 1 Pós-Graduação em Ecologia, Instituto Nacional de Pesquisas da Amazônia, Avenida André 12 Araújo, Manaus, Amazonas, Brasil, 13 14 2 Pós-Graduação em Recursos Naturais Amazônicos, Universidade Federal do Oeste do Pará, 15 Santarém, Pará, Brasil, 16 17 3 Instituto de Ciências Biológicas, Universidade Federal do Amazonas, Manaus, Amazonas, 18 Brasil 19

21 * Corresponding author

22 E-mail: [email protected] (GMP)

24 ¶These authors contributed equally to this work. 25 26 27 28 29 30 73

31 Abstract

32 Investigating the role of historical and ecological factors structuring assemblages is relevant to

33 understand mechanisms and processes affecting biodiversity across heterogeneous

34 habitats. Considering that community assembly often involves scale-dependent processes,

35 different spatial scales may reveal distinct factors structuring assemblages. In this study we use

36 lizard abundance data from 83 plots to investigate assemblage spatial structure at two distinct

37 scales in southwestern Amazonian Brazil. At a regional scale, we test the general hypothesis

38 that the Madeira River acts as a barrier to dispersal of some lizard species, which results in

39 distinct assemblages between river banks. At a local scale, we test the hypothesis that

40 assemblages are not evenly distributed across heterogeneous habitats but respond to a

41 continuum of inadequate-to-optimal portions of environmental gradients. Our results show that

42 regional lizard assemblages are structured by the upper Madeira River acting as barrier to

43 29.62% of the species sampled. This finding suggests species have been historically isolated at

44 one of the river banks, although the strength of the barrier may depend on the regional shape of

45 the river. At a local scale, different sets of environmental gradients affected assemblage

46 composition between river banks or even within a river bank. These findings indicate that

47 environmental filtering is a major cause of lizard assemblage spatial structure in the upper

48 Madeira River, but predictor variables cannot be generalized over the study area. Based on a

49 single study system we demonstrate that lizard assemblages along the forests near the banks of

50 the upper Madeira River are not randomly structured but respond to multiple factors acting at

51 different and hierarchical spatial scales.

55 Introduction

56 Investigating historical and ecological factors structuring assemblages may reveal

57 patterns of biodiversity distribution across time and space [1,2]. However, defining mechanisms

58 and processes that potentially affect assemblage structure is often highly dependent on the

59 spatial scale applied [3-5]. Such dependence results from the fact that assemblage composition

60 (e.g. taxonomic diversity) is influenced by complex hierarchical interactions among processes

61 that operate at multiple spatio-temporal scales [6]. In highly heterogeneous habitats such as the

62 Amazonian tropical rainforests the relative contribution of historical and ecological processes

63 to assemblage structuring is poorly understood for many taxa, mainly because multi-scale

64 ecological approaches depend on standardized sampling systems, which have been specifically

65 designed for such purpose [e.g. 7-12]. Regarding lizards, poor knowledge on assemblage

66 structure also results from lack of refined data on individual species distribution [13], despite

67 few unpublished studies have shown assemblage spatial structure defined by environmental

68 heterogeneity [e.g. 14-16].

69 At broad spatial scales (e.g. Amazon Basin), it has been suggested that many organisms

70 are restrictedly distributed by their inability to cross large rivers. From the classic studies of

71 Alfred R. Wallace on primate distribution across the Amazon Basin [e.g. 17], it has been known

72 that the Amazon River and some of its main tributaries (e.g. Madeira, Negro) may be important

73 biogeographic barriers to dispersal. Testing the Wallace´s hypothesis has revealed the riverine

74 barrier as a major factor explaining limited distribution of plants [18], birds [19-22], frogs

75 [23,12], primates [24,25] and spiny rats [26]. Additionally, studies have shown that gene flow

76 reduced or blocked by a riverine barrier may cause genotypic and phenotypic divergence in

77 Amazonia [27-29]. Specifically for lizards, riverine barriers may cause intraspecific genetic

78 divergence [27], although they do not necessarily produce different morphotypes [30].

79 Interspecifically, species distribution regionally limited to a single river bank may cause distinct

80 assemblage compositions between banks [12,31].

81 At local scales, environmental gradients may affect species occurrence and abundance

82 due to the filter effect of the spatial variation in habitat suitability [32,33]. In general, it is

83 expected that habitat-specialist species find inadequate-to-optimum continuums of

84 environmental conditions for survival and reproduction [34]. Environmental filtering has been

85 found in Amazonia for plants [35,36], frogs [37,38], birds [39,40], snakes [41,42] and lizards

86 [43,15]. For the latter, local assemblages may differ due to variation in individual abundance

87 or species turnover along gradients of distance from water courses [44,31], elevation [45],

88 climate seasonality [46], and number of trees [47,43]. Additionally, lizard assemblages may be

89 indirectly structured by species turnover along gradients of canopy openness affecting the

90 availability of thermoregulation sites [48,49], understory-plant density affecting the availability

91 of foraging sites for perching species [50], and clay content in the soil affecting plant

92 composition and food availability [43].

93 Integrating multiple spatial scales is relevant to estimating simultaneous effects of

94 historical and ecological factors on assemblage structure, especially in heterogeneous habitats

95 such as rainforests in Amazonia [51]. However, designing a sampling system which is efficient

96 to quantify assemblages and habitats at multiple scales may be challenging. The RAPELD [1]

97 method (Brazilian acronym for rapid sampling plus long-term ecological research) has been

98 shown to be efficient for this purpose in the region of the upper Madeira River [13], due to (i)

99 the adequate distribution of plot sets (5 km2 each) so that hypotheses based on the effects of

100 historical factors on regional assemblages may be tested (e.g. riverine barriers), and (ii) the 76

101 plots following altitudinal contours reduce within-plot environmental variation, which allows

102 them to be assumed as environmental units to test hypotheses based on environmental filtering

103 [1]. The rationale behind testing such hypotheses in southwestern Amazonia is that the Madeira

104 River has been recognized as a barrier to dispersal of Squamata reptiles, which causes species

105 turnover along a longitudinal gradient [52], and the region covers two endemism zones

106 (Rondônia e Inambari) that are distinct regarding geological history and environmental

107 heterogeneity [53].

108 In this study we use plot-based lizard abundance data from the upper Madeira River

109 (southwestern Amazonian Brazil) to investigate patterns of assemblage structure at two distinct

110 spatial scales. At a regional scale, we test the hypothesis that lizard assemblages differ between

111 the river banks. We expect differences in species composition and abundance as a consequence

112 of the Madeira River historically limiting lizard dispersal. At local scale, we test the hypothesis

113 that environmental heterogeneity causes species turnover, because species are absent or occur

114 at low densities in suboptimal portions of environmental gradients. Specifically, we quantify

115 the filtering effects on lizard abundance driven by gradients of number of trees, soil nutrient

116 composition, shrub density, elevation, clay and sand content in the soil, and distance from the

117 river bank. We expect that analyzing assemblages from two distinct perspectives will provide

118 us with deep insights into factors that cause and maintain biodiversity at megadiverse regions

119 such as the upper Madeira River.

120 Materials and methods

121 Study area

122 The study area is located near the banks of the upper Madeira River (centroid

123 coordinates 08°48004.0″ S; 63°56059.8″ W), from the outskirts of Porto Velho (Rondônia state)

124 to about 600 km upriver, in the southwestern portion of Brazilian Amazonia. We also surveyed

125 plots near the Jaci Paraná River, a tributary on the east bank of the upper Madeira River (Fig

126 1).

127

128 Fig 1. Location of the upper Madeira River, state of Rondônia, Brazil. Five km2 sampling

129 modules (circles) near the banks. Gray circles show modules in the Inambari endemism zone,

130 blue circles are modules in the Rondônia endemism zone [according to 20]. The acronyms

131 summarize sampling modules’ local names: TO = Teotônio, IB = Ilha dos Búfalos, IP = Ilha

132 das Pedras, JL = East Jirau, JR = West Jirau, JP = Jaci-Paraná, MO = Morrinhos. In detail on

133 the left side, the standard configuration of each module, with 14 plots (squares), 250 m-long

134 each, distributed along a gradient of distance from the river bank (0–5,000 m).

135

136 In this study we quantified environmental heterogeneity as continuous gradients that

137 may be broadly classified for descriptive purposes in three main habitat types. They mainly

138 differ in canopy height, soil texture, and understory-plant density and species composition

139 [following 54]. In the upland (terra-firme) forests habitats are never flooded by overflowing

140 large rivers, the canopy is 30 m high, and the understory-plant density and clay content in the

141 soil often depends on elevation [55]. The várzea forests are seasonally flooded by overflowing

142 sediment-rich rivers, which produces nutrient-rich soils that are water-saturated for long

143 periods. The canopy is 20 m high, and the understory is rich in bromeliads. The campinaranas

144 are patches of palm tree-rich forests growing on a white-sand soil, which is highly drained and

145 nutrient-poor [54].

146 The climate of the study area is tropical humid, with annual average temperature at 25.5

147 °C and average precipitation at 2,287 mm [56]. Precipitation is distributed throughout the year

148 in well-marked dry (May to September) and rainy (October to April) seasons. During the dry

149 season, small streams can dry completely [56].

150 Sampling design

151 We collected lizard abundance data in seven 5 km2 RAPELD sampling sites (hereinafter

152 modules), that were installed perpendicularly to the river bank. RAPELD [1] is a modification

153 of the Gentry´s sampling method based on 1-ha plots [57], with the main difference being that

154 the RAPELD plot central lines follow the altitudinal curves to reduce environmental variation

155 within plots (PPBio - http://ppbio.inpa.gov.br). We sampled three modules on the east bank of

156 the Madeira River (East-Jirau, Jaci-Paraná and Morrinhos), and four modules on the west bank

157 (West-Jirau, Ilha das Pedras, Ilha dos Búfalos and Teotônio). The average distance between

158 neighboring modules was 120 km. Each RAPELD module was composed of two 5-km long

159 parallel trails, separated by 1 km. We surveyed seven 250 m plots (20 m wide) on each trail,

160 totaling 98 plots (14 plots in each of the seven modules). The plots were distributed along a

161 gradient of distance from the river bank, at 0, 500, 1000, 2000, 3000, 4000 and 5000 m.

162 We were not able to find lizards in 15 plots, and the excess of zeros in the dataset

163 prevented us to reliably estimate pairwise distances among plots to summarize assemblage

164 composition (see Data analysis). Therefore, we excluded zero-valued plots and our analyzes

165 are based on 83 plots.

166 Sampling effort

167 We sampled each plot in four different periods (24 February to 26 April 2010, July 30

168 to August 19 2010, November 5 to 26 2010, and January 13 to February 4 2011) to cover large

169 portions of the regional variation in temperature and precipitation along a year. We used

170 species’ maximum abundance values per plot in the analyzes.

171 We found lizards using active visual search, with two simultaneous observers positioned

172 10 m apart. In addition, we supplemented the sampling effort by sweeping the leaf litter and

173 removing debris in a 2 m strip following the center line of the plot. This approach was

174 particularly useful to increase the efficiency of sampling fossorial and leaf-litter species (e.g.

175 Alopoglossidae, Gymnophthalmidae). The searching time in each plot varied between 40 and

176 60 minutes.

177 Environmental variables

178 We measured eight environmental gradients in each plot, attempting to quantify spatial

179 heterogeneity in habitat quality. We quantified vegetation structure by measuring (i) number of

180 trees and (ii) shrub density. Those gradients potentially affect squamates abundance by

181 influencing availability of foraging, resting and thermoregulation sites [58-60]. We also

182 measured edaphic gradients related to soil texture, fertility, and flat-level deviation, which are

183 (iii) clay content, (iv) sand content, (v) nutrient composition (Soil pH, Calcium, Magnesium,

184 Potassium, Zinc and exchangeable Aluminum), (vi) elevation, and (vii) terrain declivity. Those

185 variables potentially affect lizard abundance by causing variation in the overall primary

186 production [61] and availability of invertebrate prey [62]. Additionally, we measured (viii)

187 distance from the river bank, because it has been found as a major factor structuring plant [36]

188 and animal [31,38,39,41] assemblages in Amazonia. The methods used to measure each

189 gradient are described in detail in Appendix 1.

190 Data analysis

191 To quantify assemblage composition, we applied the Bray-Curtis index to estimate

192 pairwise distances in species abundance among plots. We reduced dimensionalities using

193 Principal Coordinate Analysis (PCoA) and represented assemblage composition by the first one

194 or two axes produced (see below). 80

195 At regional scale (riverine barrier effects) we modeled the PCoA using all data (83

196 plots). The two first axes captured 30% (PCoA 1 = 16%. PCoA 2 = 14%) of the original variance

197 in species abundance, and we used them to represent assemblage composition. To assess

198 assemblage structuring, we used Multivariate Analysis of Variance MANOVA to test

199 differences in assemblage composition (PCoA axes 1 and 2) between the river banks. We

200 implemented a MANOVA using the vegan [63] R-package [64].

201 Analyzes at regional scale revealed two distinct lizard assemblages between the river

202 banks (see Results). In addition, preliminary analyzes at local scale revealed that in two modules

203 (Ilha das Pedras and East Jirau) environmental gradients may affect assemblage composition in

204 opposite directions compared to the other modules (S2 and S3 Fig). These findings suggested

205 that the banks of the Madeira River and some of the sampling modules within a river bank are

206 distinct environmental units, which contain distinct spatial structures of lizard assemblage

207 composition. Therefore, to assess assemblage structure at local scale we modeled four distinct

208 PCoA ordinations, using data from (i) the west bank, except for the module Ilha das Pedras (37

209 plots), which captured 86% of the original variance (PCoA 1 = 0.50, PCoA 2 = 0.36); (ii) the

210 east bank, except for the module East Jirau (23 plots), which captured 45% of the original

211 variance (PCoA 1 = 0.30, PCoA 2 = 0.15); (iii) the module Ilha das Pedras (12 plots), which

212 captured 45% of the original variance (PCoA 1 = 0.32, PCoA 2 = 0.13); and (iv) the module

213 East Jirau (11 plots), which captured 85% of the original variance (PCoA 1 = 0.49, PCoA 2 =

214 0.36).

215 The environmental gradients measured are expressed in different units and therefore in

216 different orders of magnitude, so we transformed them using the “scale” function of the vegan

217 R-package. This function subtracts mean values from each variable and scales centralized

218 variables by dividing them by their standard deviation [63]. We used Mixed Linear Models to

219 test the effects of scaled environmental gradients on assemblage composition based on data

220 from multiple sampling modules. By using this method, we were able to include sampling

221 modules as random effects to minimize potential abrupt differences in environmental gradients

222 and lizard assemblages among the modules analyzed in a same model [65]. We set up two

223 different groups of mixed models, according to the assemblage compositions summarized by

224 PCoA for the west and east banks of the Madeira River. Each group was composed of as many

225 models as necessary to test all possible combinations of environmental gradients, except for

226 those that were highly correlated. For instance, clay and sand content in the soil were not used

227 in a same model because they were highly correlated on both river banks (r ≥ 0.93). In addition,

228 elevation was correlated with terrain declivity on both river banks (r ≥ 0.78) and soil-nutrient

229 composition on the east bank (r = 0.66).

230 For the two modules that were analyzed separately (Ilha das Pedras and East Jirau), it

231 was not necessary to control random effects of sampling sites, so we tested the effects of

232 environmental gradients on the assemblage composition using multiple linear regression

233 models. We tested models with assemblage composition (PCoA 1) as dependent variable, and

234 all possible combinations of uncorrelated environmental gradients as independent variables.

235 To select the most parsimonious mixed-effects and multiple-regression models we

236 ranked all the models by the Akaike´s Information Criterion corrected for few parameters [66].

237 We refined the model selection by penalizing nested models assuming ∆AICc < 2 as a cut-off

238 point. All selected models were validated by normal distribution of residuals (Shapiro-Wilk W

239 > 0.95, P > 0.05 in all cases).

240 For visually checking the distribution of lizard abundance values per species along river

241 banks and environmental gradients (only those that significantly affected assemblage

242 composition) we plotted ordinated sampling plots. These graphs will be used in this study for

243 assessing how spread the distributions of abundance values are over the river banks and the

244 environmental heterogeneity measured.

245

246 RESULTS

247 We found 27 lizard species, which are classified in 18 genera and 10 families. The most

248 frequently found species were Norops fuscoarautus (Dactyloidae), Gonatodes humeralis

249 (Sphaerodactylidae), and Ameiva ameiva (Teiidae), which occurred in both banks of the

250 Madeira River, in 55, 49 and 30% of the plots respectively. Contrarily, Alopoglossus angulatus

251 (Alopoglossidae) and Enyalius leechii (Leiosauridae) were found in one single plot (Table 1).

252

253 Table 1. List of lizard species sampled in the upper Madeira River, Brazil. N = total

254 abundance per species, East and West = Madeira river banks filled with presence (1) and

255 absence (0) data.

Family/Species N East West Dactyloidae Norops fuscoauratus (D’Orbigny, 1847) 103 1 1 Norops tandai (Wagler, 1830) 2 0 1 Norops ortonii (Cope, 1869) 2 1 1 Dactyloa punctata (Daudin, 1802) 27 1 1 Dactyloa transversalis (Dumeril, 1851) 9 0 1 Alopoglossidae Alopoglossus angulatus (Linnaeus, 1758) 2 0 1 Gymnophthalmidae Arthrosaura reticulata (O’Shaughnessy, 1881) 5 1 0 Cercosaura argula (Peters, 1863) 5 1 1 Cercosaura eigenmanni (Griffin, 1917) 11 1 1 Cercosaura bassleri (Ruibal, 1952) 8 0 1 Iphisa elegans (Gray, 1851) 8 1 1 Loxopholis percarinatum (Muller, 1923) 10 1 1 Hoplocercidae 83

Enyalioides laticeps (Guichenot, 1855) 3 1 1 Hoplocercus spinosus (Fitzinger, 1843) 2 1 1 Leiosauridae Enyalius leechii (Boulenger,1885) 2 1 0 Scincidae Copeoglossum nigropunctatum (Spix, 1825) 14 1 1 Phyllodactylidae Thecadactylus rapicauda (Houttuyn, 1782) 21 1 1 Sphaerodactylidae Chatogekko amazonicus (Andersson, 1918) 12 1 1 Gonatodes hasemani (Griffin, 1917) 29 1 1 Gonatodes humeralis (Guichenot, 1855) 432 1 1 Teiidae Kentropyx altamazonica (Cope, 1876) 14 1 1 Kentropyx calcarata (Spix, 182) 37 1 0 Kentropyx pelviceps (Cope, 1868) 29 0 1 Ameiva ameiva (Linnaeus, 1758) 48 1 1 Tropiduridae Plica plica (Linnaeus, 1758) 7 1 1 Plica umbra ochrocollaris (Spix, 1825) 21 1 1 Uranoscodon superciliosus (Linnaeus, 758) 5 1 1 Total 868 256

257 Regional assemblage structuring - Madeira River as a biogeographic barrier

258 We found 19 species on both banks of the Madeira River, which is equivalent to 70.37%

259 of the total diversity sampled. This finding suggests that most of the species sampled are widely

260 distributed throughout the study area. However, for several of the species found on both sides

261 of the river (e.g. Loxopholis percarinatum, Kentropyx altamazonica, Cercosaura eigenmanni,

262 Plica plica, Uranoscodon superciliosus, Copeoglossum nigropunctatum), plot-related

263 frequency and abundance were not even between the river banks (Fig 2). Additionally, five

264 species (18.52%) were restricted to the west bank – Alopoglossus angulatus, Norops tandai,

265 Dactyloa transversalis, Cercosaura bassleri and Kentropyx pelviceps, and three species

266 (11.11%) were restricted to the east bank –Arthrosaura reticulata, Kentropyx calcarata e

267 Enyalius leechii. These findings suggest two distinct assemblage compositions delimited by the

268 Madeira River, which is strongly supported by differences in the PCoA scores (based on 83

269 plots) between the river banks (MANOVA Pillai Trace = 0.315, F1–81 = 18.40, P <0.001).

270

271 Fig 2. Plots ordinated according to their position on the upper Madeira River (west and 272 east). The heights of the black rectangles are relative to species abundance values.

273

274 Local assemblage structuring – the role of environmental gradients

275 On the west bank of the Madeira River (except for the module Ilha das Pedras) three

276 mixed-effects models were selected by ∆AICc < 2 (Table 2). All the selected models

277 consistently returned number of trees as a major gradient affecting assemblage composition (P

278 < 0.001 in all cases). Despite some species occupied large portions of the gradient of number

279 of trees (e.g. Ameiva ameiva, Norops fuscoauratus), species absence or low abundance in

280 specific intervals between 144 and 613 trees caused species turnover (Fig 3). According to the

281 models selected, assemblage composition was not affected by elevation (P = 0.76), and soil-

282 content of sand (P = 0.84) or clay (P = 0.91).

283

284 Table 2. Summary of the results returned by Linear Mixed-Effects Models. The models

285 were set up using data from the west (Teotônio, Ilha dos Búfalos and West Jirau) and east

286 (Morrinhos and Jaci-Paraná) banks of the upper Madeira River. The models were selected by

287 AICc Δ < 2. Shapiro-Wilk tests were applied on the residuals from each model to test normality.

288 Bolded p-values show cases in which the null hypothesis was rejected.

289

Margin Fixed effects AICc Weight df t p Variance Shapiro

-Wilk

Number of 12.89 0.314 Intercept:2.18 -6.92 <0.001 54% P=0.109

Trees and Trees:3.01 18.8 <0.001 Elevation Elevation:1.43 -0.31 0.76

Sand and 12.88 0.309 Intercept:3.39 -14.69 0.001 P=0.066

Number of 69% Sand:1.86 -0.19 0.84

Trees West Trees:3.29 18.8 <0.001

Clay and 12.88 0.305 Intercept:1.00 -9.07 <0.001 P=0.153

Number of 76%

Clay:9.76 0.10 0.91 Trees Trees:3.27 18.88 <0.001

Elevation 2.0 0.412 Intercept:2.30 6.37 <0.001 P=0.782

and Margin Elevation:2.30 -6.27 <0.001 71%

distance

Margim:2.30 1.72 0.09

Number of 2.0 0.400 Intercept:2.30 5.92 <0.001 72% P=0.413 East

Trees and Trees:2.10 18.8 0.10 Elevation Elevation:2.30 -0.31 <0.001

290

291 Fig. 3. Plots ordinated according to their position relative the number of trees in the west

292 bank of the upper Madeira River, state of Rondônia, Brazil. The heights of the black

293 rectangles are relative to species abundance values.

Margins Variables AICc Weight Std. error t P F r2

Number 15.7 0.31 Intercept:8.76 0.00 1.00 2.746 0.37

of Trees Trees:9.19 0.90 0.39 and Elevation:9.19 -2.06 0.06 Elevation

Sand and 15.8 0.29 Intercept:8.81 0.00 1.00 2.66 0.37

West West Elevation Sand:9.21 0.85 0.42

Elevation:9.21 -2.18 0.05

Clay and 16.2 0.25 Intercept: 1.21 0.1 1.10 2.45 0.35

Elevation Clay:6.12 -0.64 0.53

Elevation:1.88 -1.98 0.07

Clay and 6.5 0.655 Intercept: 5.69 0.00 1.00 15.42 0.81

Distance Clay: -1.05 -1.69 0.13

from the Margim:2.89 4.63 <0.001

margin

East Sand and 7.9 0.367 Intercept: 2.30 5.92 <0.001 13.07 0.78

Distance Sand:8.81 1.28 0. 24 from the Margim:2.85 4.15 <0.001 margin

294 87

295 For the Ilha das Pedras module three multiple-regression models were selected (Table

296 3), all of them containing elevation as an independent variable. This gradient significantly

297 affected assemblage composition according to a model constructed with soil sand content as an

298 additional independent variable (P = 0.05) (Fig 4). However, the effects of elevation on the

299 assemblage composition were marginally significant in models containing number of trees (P

300 = 0.06) and soil clay content (P = 0.07) as independent variables.

301

302 Table 3. Summary of the results returned by Linear Mixed-Effects Models. The models

303 were set up using data from the Ilha das Pedras (west river bank) and East Jirau (east river bank)

304 modules for test the effects of environmental gradients on lizard assemblage composition. The

305 models were selected by AICc Δ < 2. Shapiro-Wilk tests were applied on the residuals from

306 each model to test normality. Bolded p-values show cases in which the null hypothesis was

307 rejected.

308

309

310 Fig. 4. Partials from a multiple linear model for the Ilha das Pedras module. Model for the

311 effects of the elevation and sand contents in the soil on lizard assemblage composition.

312 Assemblage composition was summarized by the first axis of an Analysis of Principal

313 Coordinates based on abundance data of the upper Madeira River, state of Rondônia, Brazil.

314 The shades of blue show values of sand content in the soil.

315

316 On the east river bank (except for the East Jirau module) two models were selected as most

317 parsimonious. Both models consistently showed strong effects of elevation on assemblage

318 composition (P < 0.001 in both cases). This finding suggests species turnover along an

319 elevational gradient of 69.12–100.59 m (Fig 5). According to the same models, distance from

320 the river bank (P = 0.09) and number of trees (P = 0.1) did not affect assemblage composition.

321

322 Fig 5. Plots ordinated according to their position relative to a gradient of elevation in the

323 east bank of the upper Madeira River, state of Rondônia, Brazil. The heights of the black

324 rectangles are relative to species abundance values.

325

326 Two multiple-regression models were selected for the East Jirau module. Both models

327 consistently returned distance from the river bank (Fig 6) as a relevant gradient affecting

328 assemblage composition (P < 0.001 in both cases). Soil-content of sand (P = 0.24) and clay (P

329 = 0.13) did not affect assemblage composition.

330

331 Fig 6. Partials from a multiple linear model to test the effects of distance from the river

332 bank, sand and clay contents in the soil on lizard assemblage composition. Assemblage

333 composition was summarized by the first axis of an Analysis of Principal Coordinates based on

334 abundance data from the East Jirau sampling module, located on the east bank of the upper

335 Madeira River, state of Rondônia, Brazil. The shades of blue show values of sand and clay

336 contents in the soil.

337

338 Discussion

339 At regional scale, we found that lizard assemblages are spatially structured by

340 differences in species composition between river banks. This finding is consistent with large

341 Amazonian rivers acting as dispersal barriers for several organisms, which have caused

342 different species subsets composed of plants [18], birds [19,21], primates [24] and diurnal frogs

343 [12]. At local scale, we showed that lizard assemblages are spatially structured by species

344 turnover along environmental gradients. However, a set of environmental gradients cannot be

345 assumed as generalized predictors among sampling sites. Our overall results are broadly

346 consistent with frog assemblages sampled in the same plots [12], which suggests multi-taxa

347 ecological patterns. We relied on a single dataset to provide understanding about assemblage

348 structure based on interacting historical and ecological processes. Therefore, we highlight the

349 relevance of investigating multi-scale assemblage structuring for ecology and conservation

350 decision making.

351 In the upper Madeira River, assemblage divergence between river banks has been

352 attributed to historical processes regionally reducing species dispersal [12]. Approximately

353 50% of the species composing a frog assemblage (13 species) were absent in one of the river

354 banks. The smaller proportion of regionally isolated lizard species (29.63%) is reasonably

355 explained by the lower dispersal capacity of small and site-attached frogs compared with most

356 lizards. Nonetheless, we investigated aseemblages in which about 30% of the sampled species

357 were isolated by the river, and another 30% of the species occurred at low relative frequency

358 or abundance at one of the river banks. This was a sufficiently adequate scenario to assume the

359 river as a historical factor segregating assemblages between the river banks. We highlight that

360 most of regionally isolated species in our sample are widely distributed throughout Amazonia

361 outside our study area [13]. Such inconsistency may be explained by the strength of the river

362 as a dispersal barrier varying along the river course, or even being nullified in response to

363 meandering shapes [67- 69,30]. Additionally, the barriers may be seasonal, because bridges for

364 stepping-stone dispersal may be revealed during the dry season, which allows gene flow

365 between river banks [70]. Therefore, our results for assemblage structure at regional scale

366 should not be extrapolated to unsampled stretches of the Madeira River or other Amazonian

367 rivers, because lizards probably have found multiple dispersal routes through evolutionary time

368 [27].

369 The isolation of species on one of the river banks may be related to the

370 geomorphological heterogeneity of the Madeira River across our study area. The Madeira river

371 flows over an incisive fluvial valley, with predominantly crystalline and a geologically ancient

372 basement (ca. 16 Ma). The morphodynamical development was mainly influenced by the

373 geomorphological and climatic changes resulting from the Andean Orogeny in the Cenozoic

374 [71], which have produced a relatively stable course along recent geological times [72]. Such

375 stability in the shape of the river course has prevented meandering across most of the study

376 area, which could facilitate for species to cross the river [73]. Exceptionally, the modules

377 located further upstream (East and West Jirau) have rocky outcrops that are exposed in the

378 middle of the river course during the dry season, which can act as bridges for stepping-stone

379 dispersal (field observation). Although lizard species used alternative dispersal routes to

380 widespread their distribution throughout Amazonia, our study showed that they were regionally

381 prevented from colonizing or maintaining populations on both banks of the upper Madeira

382 River.

383 At local scale, lizard assemblages were spatially structured by environmental filtering

384 causing non-random assemblage composition. Environmental conditions selected species that

385 were able to survive and maintain viable conditions in given sampling plots [74]. Despite we

386 sampled species that are generalist in relation to the environmental gradients measured (e.g.

387 Ameiva ameiva, Norops fuscoauratus), species for which distributions were restricted to narrow

388 regions of gradients (e.g. Cercosaura argula, Norops ortonii, Uranoscodon superciliosus)

389 caused species turnover across sampling plots. Species turnover mediated by environmental

390 filtering is a major factor structuring local assemblages in Amazonia [e.g. 41,36,39], and in the

391 upper Madeira River it has efficiently explained assemblage structure in bats [75], frogs [12]

392 and snakes [76]. However, we cannot generalize a single environmental dataset as a predictor

393 for assemblage composition in all plots. Environmental predictors for assemblage composition

394 differed between the river banks or even within a river bank. This finding suggests that the scale

395 at which lizard assemblages respond to environmental heterogeneity may be more refined than

396 the classification of the Madeira river banks as distinct endemism zones [77,20].

397 Number of trees was a major factor causing species turnover in the west bank of the

398 Madeira River. This gradient ranged from 144 to 613 trees, which shows that the vegetation

399 structure is quite heterogeneous throughout our study area. Heterogeneity in vegetation

400 structure affects species occurrence and abundance due to variation in the availability of

401 foraging, nesting, resting, and thermoregulating sites [58,60]. Additionally, tree cover may

402 directly affect food availability, protection against predators, light intensity, temperature,

403 humidity and wind speed [59,60]. The evidence for assemblage structuring along a gradient of

404 number of trees is of concern from a conservation point of view, because our study area has

405 been intensely deforested by the agribusiness and large hydroelectric plants [78]. It is widely

406 expected that species dependent on high levels of tree cover (e.g. Norops tandai, Norops ortonii,

407 Dactyloa transversalis) will either be locally extinct or migrate to more suitable habitats. Future

408 studies should focus on investigating species turnover at time scales.

409 We found species turnover along an elevational gradient, although this finding was most

410 evident on the east bank of the Madeira River. On the east bank the plots were installed on the

411 depression of the Ji-Paraná river, which generated elevation values below 30 m. Low elevation

412 is often related to outcropping of groundwater and high drainage density [79,71], which favors

413 the occurrence of habitat-specific species for high humidity. For instance, Arthrosaura

414 reticulata and Uranoscodon superciliosus typically occupy humid low areas [80,81], and in this

415 study those species were found only on the east bank of the Madeira River. Additionally,

416 elevation indirectly influences assemblage composition because it affects water availability and

417 soil fertility [82-84], and therefore the overall structure of available habitats [85]. Extreme

418 variation in elevation may cause behavioral and morphological differentiation in Andean lizards

419 [86]. In this study we showed that even subtle variation in elevation (24 to 128 m) may be

420 sufficient for species to be locally filtered. A similar finding was observed using frog

421 assemblage data from the Guiana Shield [11,37].

422 The gradient of distance from the river caused species turnover in the East Jirau module.

423 Although habitats may be classified in riparian and non-riparian zones [87], gradients of

424 distance from water courses carry multiple continuous interacting variables of microclimate,

425 nutrient availability, vegetation cover and edaphic structure. Habitats continuously changing

426 along gradients of distance from streams (< 12 m wide) have caused species turnover structuring

427 plant [36], frog [38], bird [39] and snake [41] assemblages. In this study, we showed a similar

428 pattern using lizard abundance data, with the main difference being that the gradient we

429 measured refers to the distance from the bank of one of the major tributaries of the Amazon

430 River. However, no significant effect of distance from the river on assemblage composition was

431 returned using data from the other modules. This finding suggests that assemblages diverging

432 between riparian and non-riparian zones should not be generalized in relation to large rivers, or

433 assemblage segregation should occur at distances that are greater than 5 km away from the river

434 bank.

435 Some of the results found may be associated to environmental variables that were not

436 explicitly measured in this study. For example, Hoplocercus spinosus (Hoplocercidae) occurred

437 on both banks of the Madeira River but occurrence was restricted to plots with rocky outcrops.

438 Such condition was only found in the westernmost sampling modules of the study area (East

439 and West Jirau), where the species finds optimal availability of thermoregulation and refuge

440 sites [88]. This finding reflects relationships between species and habitats that are dependent of

441 biological traits affecting survival [89,90] and dispersal capacity [91,92], such as body size, diet

442 [93], specificity level in habitat use [81], reproductive [49] and foraging mode [76]. Therefore,

443 although patterns of assemblage structure are usually described based on dissimilarities among

444 plots regarding subsets of cooccurring species, they may be determined by ecological

445 requirements of individual species.

446 We showed that lizard assemblages in the upper Madeira River are structured by scale-

447 dependent hierarchical factors. Historical processes related to the Andes uplift [94] have

448 isolated regional assemblages between the river banks, and have also generated distinct habitat

449 patches, which in turn generate distinct local lizard assemblages. It is generally well established

450 that interacting historical and environmental factors explain hierarchical structures of

451 assemblages [5]. However, empirical application is not common because it relies on efficient

452 sampling designs to capture multiple scales. In the megadiverse Amazonian rainforests this has

453 been achieved by a few studies [73,12,31]. Considering the fine levels in which such studies

454 assessed processes affecting biodiversity, efficient methods for multi-scale sampling should be

455 prioritized by ecology and conservation biology.

456

457

458 Acknowledgments

459 Data collection was logistically supported by Programa de Pesquisas em Biodiversidade

460 (PPBio), Centro de Estudos Integrados da Biodiversidade Amazônica (INCT-CENBAM), and

461 Programa de Conservação da Vida Selvagem da Santo Antônio Energia S.A. Conselho

462 Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de 94

463 Aperfeiçoamento de Pessoal de Nível Superior (CAPES) granted PhD scholarships to GMP.

464 CAPES provided a PNPD postdoc grant to RF and CNPq provided productivity grants to ILK

465 and APL. We collected data under RAN-ICMBio / IBAMA permit nº 13777-2.

466

467 References

468 1. Magnusson WE, Braga-Neto R, Pezzini F, Baccaro F, Bergallo H, Penha J, et al.

469 Biodiversidade e monitoramento ambiental integrado: o sistema Rapeld na Amazônia.

470 First ed. Santo André- SP: Attema Editorial; 2013. Available from:

471 https://ppbio.inpa.gov.br/sites/default/files/Biodiversidade_e_monitoramento_ambie

472 ntal_integrado.pdf. cited 10 March 2019.

473 2. Pianka ER. Ecology and natural history of desert lizards: analyses of the ecological

474 niche and community structure. New Jersey. Princeton University Press; 1986.

475 3. Schneider DC. The rise of the concept of scale in Ecology. Bioscience. 2001; 51: 545–

476 556. doi: 10.1641/0006-3568(2001)051[0545:TROTCO]2.0.CO;2.

477 4. Gaston KJ, Blackburn TM. Macroecology and conservation biology. In: Blackburn

478 TM, Gaston KJ, editors. Macroecology: Concepts and consequences. Oxford:

479 Blackwell Science; 2003. pp. 345–367.

480 5. Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010; 85: 183–

481 206. doi: 10.1086/652373; PMID: 20565040.

482 6. Antonelli A, Quijada-Mascareñas A, Crawford AJ, Bates JM, Velazco PM, Wüster

483 W. Molecular studies and phylogeography of Amazonian tetrapods and their relation

484 to geological and climatic models. In: Hoorn C, Wesselingh FP, editors. Amazonia,

485 landscape and species evolution: a look into the past: Blackwell Publishing; 2010. pp.

486 386–404.

487 7. Buhrnheim CM, Cox-Fernandes C. Structure of fish assemblages in Amazonian Rain-

488 Forest Streams: Effects of habitats and locality. Copeia. 2003; 2: 255–262. doi:

489 10.1643/0045-8511(2003)003[0255:SOFAIA]2.0.CO;2.

490 8. Barros OG, Cintra R. The effects of forest structure on occurrence and abundance of

491 three owl species (Aves: Strigidae) in the Central Amazon Forest. Rev Bras Zoo.

492 2009; 26: 86–95. doi: 10.1590/S1984-46702009000100014.

493 9. Costa FRC, Magnusson WE, Luizão RC. Mesoscale distribution patterns of

494 Amazonian understorey herbs in relation to topography, soil and watersheds. J Ecol.

495 2005; 93: 863–878. doi: 10.1111/j.1365-2745.2005.01020.x.

496 10. Haugaasen T, Peres CA. Mammal assemblage structure in Amazonian floodedand

497 unflooded forests. J Trop Ecol. 2005; 2: 133–145. doi: 10.1017/S026646740400207X.

498 11. Menin M, Waldez F, Lima AP. Effects of environmental and spatial factors on the

499 distribution of anuran species with aquatic reproduction in central Amazonia.

500 Herpetol J. 2011; 21: 255–261.

501 12. Dias-Terceiro RG, Kaefer IL, Fraga R, Araújo MC, Simões PI, Lima AP. A matter of

502 scale: historical and environmental factors structure anuran assemblages from the

503 upper Madeira River, Amazonia. Biotropica. 2015; 47: 259–266. doi:

504 10.1111/btp.12197.

505 13. Ribeiro-Júnior MA. Catalogue of distribution of lizards (Reptilia: Squamata) from the

506 Brazilian Amazonia. I. Dactyloidae, Hoplocercidae, Iguanidae, Leiosauridae,

507 Polychrotidae, Tropiduridae. Zootaxa. 2015; 3983: 001–110. doi:

508 10.11646/zootaxa.3983.1.1.

509 14. Lobão PSP. Associações no uso do habitat por cinco espécies de lagartos amazônicos.

510 M.Sc. Thesis, Instituto Nacional de Pesquisas da Amazônia. 2008. Available from:

511 https://bdtd.inpa.gov.br/handle/tede/731. cited 10 March 2019.

512 15. Moraes LFP. Diversidade beta em comunidades de lagartos em duas Ecorregiões

513 distintas na Amazônia. M.Sc. Thesis, Instituto Nacional de Pesquisas da Amazônia,

514 Manaus. 2008. Available from: https://bdtd.inpa.gov.br/handle/tede/736. cited 10

515 March 2019.

516 16. Bittencourt S. A insularização como agente de fragmentação florestal em

517 comunidades de lagartos da Amazônia Central. M.Sc. Thesis, Instituto Nacional de

518 Pesquisas da Amazônia. 2008. Available from:

519 https://bdtd.inpa.gov.br/handle/tede/1846. cited 15 March 2019.

520 17. Wallace AR. On the monkeys of the Amazon. J Nat Hist. 1952; 14 (2): 451–454. doi:

521 10.1080/037454809494374.

522 18. Dexter KG, Terborgh JW, Cunningham CW. Historical effects on beta diversity and

523 community assembly in Amazonian trees. PNAS. 2012; 109: 7787–7792. doi:

524 10.1073/pnas.1203523109.

525 19. Hayes FE, Sewlal JN. The Amazon River as a dispersal barrier to passerine birds:

526 effects of river width, habitat and taxonomy. J Biogeogr. 2004; 31: 1809–1818. doi:

527 10.1111/j.1365-2699.2004.01139. x.

528 20. Ribas CC, Aleixo A, Nogueira ACR, Miyaki CY, Cracraft J. A palaeobiogeographic

529 model for biotic diversification within Amazonia over the past three million years.

530 Proc Bio Sci. 2012; 279: 681–689. doi: 10.1098/rspb.2011.1120.

531 21. Pomara LY, Ruokolainen K, Young KR. Avian species composition across the

532 Amazon River: the roles of dispersal limitation and environmental heterogeneity. J

533 Biogeogr. 2014; 41: 784–796. doi: 10.1111/jbi.12247.

534 22. Fernandes AM, Gonzalez J, Wink M, Aleixo A. Multilocus phylogeography of the

535 Wedge-billed Woodcreeper Glyphorynchus spirurus (Aves, Furnariidae) in lowland

536 Amazonia: Widespread cryptic diversity and paraphyly reveal a complex

537 diversification pattern. Mol Phylogenet Evol. 2013; 66(1): 270–282. doi:

538 10.1016/j.ympev.2012.09.033.

539 23. Simões PI, Lima AP, Magnusson WE. Acoustic and morphological differentiation in

540 the frog Allobates femoralis: Relationships with the upper Madeira river and other

541 potential geological barriers. Biotropica. 2008; 40: 607–614. doi: 10.1111/j.1744-

542 7429.2008.00416.x.

543 24. Ayres JM, Clutton-Brock TH. River boundaries and species range size in Amazonian

544 primates. Am Nat. 1992; 140: 531–537. doi: 10.1086/285427.

545 25. Boubli JP, Ribas C, Alfaro JWL, et al. Spatial and temporal patterns of diversification

546 on the Amazon: A test of the riverine hypothesis for all diurnal primates of Rio Negro

547 and Rio Branco in Brazil. Mol Phylogenet Evol. 2015; 82: 400–412. doi:

548 10.1016/j.ympev.2014.09.005.

549 26. Patton JL, da Silva MNF, Malcolm JR. Gene genealogy and differentiation among

550 arboreal spiny rats (Rodentia: Echimyidae) of the Amazon Basin: a test of the riverine

551 barrier hypothesis. Evol Lett. 1994; 48: 1314–1323. doi: 10.1111/j.1558-

552 5646.1994.tb05315.x.

553 27. Ávila-Pires TC, Mulcahy DG, Werneck FP, Sites-Jr JW. Phylogeography of the teiid

554 lizard Kentropyx calcarata and the Sphaerodactylid Gonatodes humeralis (Reptilia:

555 Squamata): testing a geological scenario for the lower Amazon-Tocantins Basins,

556 Amazonia, Brazil. Herpetologica. 2012; 68: 272–287. doi:

557 10.1655/HERPETOLOGICA-D-11-00021.1.

558 28. Kaefer IL, Tsuji-Nishikido BM, Mota EP, Farias IP, Lima AP. The early stages of

559 speciation in Amazonian forest frogs: phenotypic conservatism despite strong genetic

560 structure. Evol Biol. 2013; 40: 228–245. doi: 10.1007/s11692-012-9205-4.

561 29. Maia GF, Lima AP, Kaefer IL. Not just the river: genes, shapes, and sounds reveal

562 population-structured diversification in the Amazonian frog Allobates tapajos

563 (Dendrobatoidea). Biol J Linn Soc Lond. 2017; 121: 95–108. doi:

564 10.1093/biolinnean/blw017.

565 30. Souza SM, Rodrigues MT, Cohn-Haft M. Are Amazonia rivers biogeographic barriers

566 for lizards? A study on the geographic variation of the spectacled lizard Leposoma

567 osvaldoi Ávila-Pires (Squamata, Gymnophthalmidae). J Herpetol. 2013; 47:511–519.

568 doi: 10.1670/12-124.

569 31. Moraes LJ, Pavan D, Barros MC, Ribas CC. The combined influence of riverine

570 barriers and flooding gradients on biogeographical patterns for amphibians and

571 squamates in south‐eastern Amazonia. J Biogeogr. 2016; 43(11): 2113–2124. doi:

572 10.1111/jbi.12756.

573 32. Mariac C, Jehin L, Saïdou AA, Thuillet AC, Couderc M, Sire P, et al. Genetic basis

574 of pearl millet adaptation along an environmental gradient investigated by a

575 combination of genome scan and association mapping. Mol Ecol. 2011; 20(1): 80–91.

576 doi: 10.1111/j.1365-294X.2010.04893.x.

577 33. Hangartner S, Laurila A, Räsänen K. Adaptive divergence in moor frog (Rana arvalis)

578 populations along an acidification gradient: inferences from QST–FST correlations.

579 Evol Letters. 2012; 66(3): 867–881. doi: 10.1111/j.1558-5646.2011.01472.x.

580 34. Kinupp VF, Magnusson WE. Spatial patterns in the understorey shrub genus

581 Psychotria in central Amazonia: effects of distance and topography. J Trop Ecol.

582 2005; 21: 363–374. doi: 10.1017/S0266467405002440.

583 35. Emilio T, Quesada CA, Costa FRC, Magnusson WE, Schietti J, Feldpausch TR, et al.

584 Soil physical conditions limit palm and tree basal area in Amazonian forests. Plant

585 Ecol Divers. 2013; 7: 215–229. doi: 10.1080/17550874.2013.772257.

586 36. Drucker DP, Costa FRC, Magnusson WE. How wide is the riparian zone of small

587 streams in tropical forests? A test with terrestrial herbs. J Trop Ecol. 2008; 24: 65–74.

588 doi: 10.1017/S0266467407004701.

589 37. Ribeiro-Jr JW, Lima AP, Magnusson WE. The effect of Riparian Zones on species

590 diversity of frogs in Amazonian Forests. Copeia. 2012; 3: 375–381. doi: 10.1643/CE-

591 11-117.

592 38. Rojas-Ahumada DP, Landeiro VL, Menin M. Role of environmental and spatial

593 processes in structuring anuran communities across a tropical rain forest. Austral Ecol.

594 2012; 37: 865–873. doi: 10.1111/j.1442-9993.2011.02330.x.

595 39. Bueno AS, Bruno RS, Pimentel TP, Sanaiotti TM, Magnusson WE. The width of

596 riparian habitats for understory birds in an Amazonian forest. Ecol Appl. 2012; 22(2):

597 722–734. doi: 10.1890/11-0789.1.

598 40. Menger J, Magnusson WE, Anderson MJ, Schlege M, Pe'er G, Henle K.

599 Environmental characteristics drive variation in Amazonian understorey bird

600 assemblages. PLoS ONE. 2017; 2(2): e0171540. doi: 10.1371/journal.pone.0171540.

100

601 41. Fraga R, Lima AP, Magnusson WE. Mesoscale spatial ecology of a tropic snake

602 assemblage: the width of riparian corridors in central Amazonia. Herpetol J. 2011; 21:

603 51–57.

604 42. Fraga R, Ferrão M, Stow AJ, Magnusson WE, Lima AP. Different environmental

605 gradients affect different measures of snake β-diversity in the Amazon rainforests.

606 PeerJ. 2018; 6: e5628. doi: 10.7717/peerj.5628.

607 43. Pinto MGM. Diversidade Beta, métodos de amostragem e influência de fatores

608 ambientais sobre uma comunidade de lagartos na Amazônia Central. M.Sc. Thesis,

609 Instituto Nacional de Pesquisas da Amazônia. 2006. Available from:

610 https://bdtd.inpa.gov.br/handle/tede/947. cited 15 March 2019.

611 44. Faria AS, Menin M, Kaefer IL. Riparian zone as a main determinant of the structure

612 of lizard assemblages in upland Amazonian forests. Austral Ecol. 2019; 1: 1–9. doi:

613 10.1111/aec.12754.

614 45. Fauth JF, Crother BI, Slowinski EJB. Elevational patterns of species richness,

615 evenness, and abundance of the Costa Rican leaf-litter herpetofauna. Biotropica.1989;

616 21: 178–185. doi: 10.2307/2388708.

617 46. Lieberman SS. Ecology of a leaf litter herpetofauna of a neotropical rain litter in

618 functioning of forest ecosystems. Biol Rev. 1986; 81: 1–31.

619 47. Driscoll DA. Extinction and outbreaks accompany fragmentation of a reptile

620 community. Ecol Appl. 2004; 14: 220–240. doi: 10.1890/02-5248.

621 48. Vitt LJ, Blackburn DG. Ecology and life history of the viviparous lizard Mabuya

622 bistriata (Scincidae) in the Brazilian Amazon. Copeia. 1999; 916–927. doi:

623 10.2307/1446087.

101

624 49. Vitt LJ, Zani PA, Lima AP. Heliotherms in tropical rain forest: the ecology of

625 Kentropyx calcarata (Teiidae) and Mabuya nigropunctata (Scincidae) in the Curuá-

626 Una of Brazil. J Trop Ecol. 1997; 13: 199–220. doi: 10.1017/S0266467400010415.

627 50. Dixo MBO. Efeito da fragmentação da floresta sobre a comunidade de sapos e lagartos

628 de serapilheira no sul da Bahia. M.Sc. Thesis. Instituto de Biociências da Universidade

629 de São Paulo. 2001.

630 51. Aleixo A. Knowledge gaps, research priorities, and future perspectives on bird

631 conservation in the Brazilian Amazon. In: De Luc AC, Devele PE, Benck GA, Goerck

632 JM, editors. Áreas importantes para a Conservação das Aves no Brasil. Parte II-

633 Amazônia, Cerrado e Pantanal. 1nd ed. São Paulo -SP: Save Brasil; 2009. pp. 59-69.

634 52. Ávila-Pires TCS, Vitt LJ, Sartorius SS, Zani PA. Squamata (Reptilia) from four sites

635 in southern Amazonia, with a biogeographic analysis of Amazonian lizards. Bol Mus

636 Para Emílio Goeldi Cienc Nat. 2009; 4(2): 99–118.

637 53. Schietti J, Martins D, Emilio T, Souza PF, Levis C, Baccaro FB. Forest structure along

638 a 600 km transect of natural disturbances and seasonality gradients in central-southern

639 Amazonia. J Ecol. 2016; 104(5): 1335–1346. doi: 10.1111/1365-2745.12596.

640 54. Cavalcante MMA. Hidroelétricas do Rio Madeira - RO: território, tecnificação e meio

641 ambiente. M.Sc. Thesis, Universidade Federal do Paraná. 2012.

642 55. IBGE Instituto Brasileiro de Geografia e Estatística. Recursos naturais e meio

643 ambiente: uma visão do Brasil. Rio de Janeiro: IBGE; 1997. Available from:

644 http://biblioteca.ibge.gov.br/biblioteca-catalogo.html?id=27704&view=detalhes.

645 cited 10 April 2019.

102

646 56. Bezerra RB, Trindade AG. Caracterização de parâmetros pluviométricos, térmicos do

647 balanço hídrico climatológico e desmatamento de Porto Velho – RO. Geografia. 2006;

648 15(1): 65-80. doi: 10.5433/2447-1747.2006v15n1p65.

649 57. Gentry AH. Changes in plant community diversity and floristic composition on

650 environmental and geographical gradients. Ann Mo Bot Gard. 1988; 75: 1–34. doi:

651 10.2307/2399464.

652 58. Burger J, Zappalorti RT. Nest site selection by Pine Snakes, Pituophis melanoleucus,

653 in the New Jersey Pine Barrens. Copeia.1986; (1): 116–121.

654 59. Webb JK, Shine R. Out on a limb: conservation implications of tree-hollow use by a

655 threatened snake species (Hoplocephalus bungaroides: Serpentes, Elapidae). Biol

656 Conserv. 1997; 81(12): 21–33. doi: 10.1016/S0006-3207(96)00160-7.

657 60. Pringle RM, Webb JK, Shine R. 2003. Canopy structure, microclimate, and habitat

658 selection by a nocturnal snake, Hoplocephalus bungaroides. Ecology. 2003; 84(10):

659 2668–2679. doi: 10.1890/02-0482.

660 61. Cintra BBL, Schietti J, Emilio T, Martins D, Moulatlet G, Souza P, et al. Soil physical

661 restrictions and hydrology regulate stand age and wood biomass turnover rates of

662 Purus-Madeira interfluvial wetlands in Amazonia. Biogeosciences. 2013; 10: 7759–

663 7774. doi: 10.5194/bg-10-7759-2013.

664 62. Franklin E, Magnusson WE, Luizão FJ. Relative effects of biotic and abiotic factors

665 on the composition of soil invertebrates’ communities in an Amazonian savannah.

666 Appl Soil Ecol. 2005; 29: 259–273. doi: 10.1016/j.apsoil.2004.12.004.

667 63. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan:

668 Community Ecology Package. R package version 1.17-1. 2010. Available from:

669 http://CRAN.Rproject.org/package=vegan. cited 2 March 2019.

103

670 64. R Core Team. R: A language and environment for statistical computing. Vienna,

671 Austria: R Foundation for Statistical Computing. 2019. Available from: https://cran.r-

672 project.org/doc/manuals/r-release/fullrefman.pdf. cited 2 March 2019.

673 65. Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics. 1982;

674 38: 963–974.

675 66. Hurvich CM, Tsai CL. Regression and time series model selection in small

676 samples. Biometrics. 1989; 76(2): 297–307. doi: 10.1093/biomet/76.2.297.

677 67. Gascon C, Lougheed SC, Bogart JP. Genetic and morphological variation in

678 Vanzolinius discodactylus: a test of the river hypothesis of speciation. Biotropica.

679 1996; 28: 376–387. doi: 10.2307/2389201.

680 68. Smith AL, Bull CM, Gardner MG, Driscoll DA. Life history influences how fire

681 affects genetic diversity in two lizard species. Mol Ecol. 2014; 23: 2428–2441. doi:

682 10.1111/mec.12757.

683 69. Dambros CS, Azevedo RA, Gotelli NJ. Isolation by distance, not rivers, control the

684 distribution of termite species in the Amazonian rain forest. Ecography. 2016; 39: 1–

685 9. doi: 10.6084/m9.figshare.1319582.v10.

686 70. Gibbs HL, Sovic M, Amazonas D, Chalkidis H, Salazar-Valenzuela D, Moura-Da-

687 Silva AM. Recent lineage diversification in a venomous snake through dispersal

688 across the Amazon River. Biol J Linn Soc Lond. 2018; 123(3): 651–665. doi:

689 10.1093/biolinnean/blx158.

690 71. Souza-Filho PWM, Quadros MLES, Scandolara JE, da Silva-Filho EP, Reis MR.

691 Compartimentação morfoestrutural e neotectônica do sistema fluvial Guaporé-

692 Mamoré-alto Madeira, Rondônia-Brasil. Braz J Geol. 1999; 29: 469–476. doi:

693 11005/10461.

104

694 72. Tikuka MM. Geoarqueologia e paleohidrologia da planície aluvial holocênica do rio

695 Madeira entre Porto Velho e Abunã/RO. Amazon. Rev Antrop. 2012; 4: 252–257.

696 73. Gascon C, Malcolm JR, Patton JL, da Silva MNF, Bogart JP, Lougheed SC, et al.

697 Riverine barriers and the geographic distribution of Amazonian species. PNAS. 2000;

698 97: 13672–13677. doi: 10.1073/pnas.230136397.

699 74. Kraft NJB, Adler PB, Godoy O, James EC, Fuller S, Levine JM. Community

700 assembly, coexistence and the environmental metaphor. Funct Ecol. 2014; 29: 592–

701 599. doi: 10.1111/1365-2435.12345.

702 75. Bobrowiec PED, Tavares VdC. Establishing baseline biodiversity data prior to

703 hydroelectric dam construction to monitoring impacts to bats in the Brazilian Amazon.

704 PloS ONE. 2017; 12(9): e0183036. doi: 10.1371/journal.pone.0183036.

705 76. Fraga RD, Lima AP, Magnusson WE, Ferrão M, Stow AJ. Contrasting patterns of

706 gene flow for Amazonian snakes that actively forage and those that wait in ambush. J

707 Heredity. 2017; 108(5): 524–534. doi: 10.1093/jhered/esx051.

708 77. Silva JMC, Rylands AB, Fonseca GAB. The fate of the Amazonian areas of

709 endemism. Conserv Biol. 2005; 19: 689–694. doi: 10.1111/j.1523-

710 1739.2005.00705.x.

711 78. Fearnside MP. Brazil's Madeira River dams: A setback for environmental policy in

712 Amazonian development. Water Altern. 2014; 7: 256–269.

713 79. Bernardi JVE, Lacerda LD, Dórea JG, et al. Aplicação da análise das componentes

714 principais na ordenação dos parâmetros físico-químicos no alto Rio Madeira e

715 afluentes, Amazônia Ocidental. Geochim Brasiliensis. 2012; 23: 79–90.

105

716 80. Hoogmoed MS, Ávila-Pires TC. Studies on the species of the South American lizard

717 genus Arthrosaura Boulenger (Reptilia: Sauria: Teiidae), with the resurrection of two

718 species. Zool Meded. 1992; 66(35): 453–484.

719 81. Vitt LJ, Zani PA, Espósito MC. Historical ecology of Amazonian lizards: implications

720 for community ecology. Oikos. 1999; 87: 286–294. doi: 10.2307/3546743.

721 82. Daws M, Mullins C, Burslem D, Paton S, Dalling J. Topographic position affects the

722 water regime in a semideciduous tropical forest in Panama. Plant Soil Environ. 2002;

723 238: 79–90. doi: 10.1023/A:1014289930621.

724 83. Fischer J, Lindenmayer DB. The sensitivity of lizards to elevation: A case study from

725 south-eastern Australia. Divers Distrib. 2005; 11: 225–233. doi: 10.1111/j.1366-

726 9516.2005.00139.x.

727 84. Pansonato MP, Costa FRC, Castilho CV, Zuquim G. Spatial scale or amplitude of

728 predictors as determinants of the relative importance of environmental factors to plant

729 community structure. Biotropica. 2013; 45: 299–307. doi: 10.1111/btp.12008.

730 85. Tews J, Brose U, Grimm V, Tielborger K, Wichmann MC, Schwager M, et al. Animal

731 species diversity driven by habitat heterogeneity/diversity: the importance of keystone

732 structures. J Biogeogr. 2004; 31: 79–92. doi: 10.1046/j.0305-0270.2003.00994.x.

733 86. Ballinger RE. Intraspecific variation in demography and life history of the lizard,

734 Sceloporus jarrovi, along an altitudinal gradient in southeastern Arizona. Ecology.

735 1979; 60: 901–909. doi: 10.2307/1936858.

736 87. Naiman RJ, Decamps H, Pollock M. The roles of riparian corridors in maintaining

737 regional biodiversity. Ecol Appl. 1993; 3: 209–212. doi: 10.2307/1941822.

106

738 88. Rocha CFD. Introdução à ecologia de lagartos brasileiros. In: Nascimento LB,

739 Bernerdes AT, Cotta GA, editors. Herpetologia no Brasil. 1nd ed. Minas Geirais, BR:

740 PUCMG, Fundação biodiversidade and Fundação Ezequiel Dias; 1994. pp. 1–68.

741 89. Richardson JL. Divergent landscape effects on population connectivity in two co-

742 occurring amphibian species. Mol Ecol. 2012; 21: 4437–4451. doi: 10.1111/j.1365-

743 294X.2012.05708.x.

744 90. Fouquet A, Courtois EA, Baudain D, Lima JD, Souza SM, Noonan DP, et al. The

745 trans-riverine genetic structure of 28 Amazonian frog species is dependent on life

746 history. J Trop Ecol. 2015; 31: 361–373. doi: 10.1017/S0266467415000206.

747 91. Brandt R, Navas CA. Life-history evolution on Tropiduridae lizards: influence of

748 lineage, body size and climate. PLoS ONE. 2011; 6: e20040. doi:

749 10.1371/journal.pone.0020040.

750 92. Cole EM, Bustamante MR, Almeida-Reinoso D, Funk WC. Spatial and temporal

751 variation in population dynamics of Andean frogs: Effects of forest disturbance and

752 evidence for declines. Glob Ecol Conserv. 2014; 1: 60–70. doi:

753 10.1016/j.gecco.2014.06.002.

754 93. Vitt LJ, Carvalho CMD. Life in the trees: the ecology and life history of Kentropyx

755 striatus (Teiidae) in the Lavrado area of Roraima, Brazil, with comments on the life

756 histories of tropical teiid lizards. Can J Zool. 1992; 70(10): 1995–2006. doi:

757 10.1139/z92-270.

758 94. Hoorn C, Wesselingh FP, Ter Steege H, Bermudez MA, Mora A, Sevink J, et al.

759 Amazonia through time: Andean uplift, climate change, landscape evolution, and

760 biodiversity. Science. 2010; 330(6006): 927–931. doi: 10.1126/science.1194585.

761

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762 Supporting information captions

763 S1 Text. Protocols for measuring the environmental gradients. Gradients used as

764 independent variables in the ecological models to test lizard assemblage structuring in the upper

765 Madeira River, Amazonian Brazil.

766 S2 Fig 1. Partials from Mixed Linear Models for the west bank of the Madeira River. Test

767 the effects of environmental gradients on lizard assemblages composition (PCoA axis 1). The

768 models were selected by ΔAICc < 2. (A) Ilha das Pedras (B) Ilha dos Búfalos (C) Jirau-West

769 (D) Teotônio.

770 S3 Fig 2. Partials from Mixed Linear Models for the East bank of the Madeira River. Test

771 the effects of environmental gradients on lizard assemblages composition (PCoA axis 1). The

772 models were selected by ΔAICc < 2. (A) Jaci- Paraná (B) Jirau-East (C) Morrinhos.

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Figures

Figure 1.

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Figure 2.

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Figure 3.

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Figure 4.

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Figure 5.

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Figure 6.

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S 1. Protocols

NUMBER OF TREES. –The density sampling method used transects that varied in size depending on the size of the plant class being surveyed, as follows: (Transect 1) plants with a diameter at breast height (DBH) ≥ 1 cm were sampled in 1m-wide band to the left side of the centerline, for the entire length of the sample plot; (Transect 2) plants with DBH ≥ 10 cm were sampled in a 20m wide band, with 10 m on either side of the plot center line. On the left, this band included Transects 1 and 3; (Transect 3) plants with DBH ≥ 30 cm were sampled in a range of 40 m wide, 20 m being on each side of the center line of the plot. On the left, this range overlapped with Transects 1 and 2, where all plants with DBH greater than or equal to 1 or 10 cm were measured. On the right side, this band includes Transect 2. More details of the plant data collection component are available at: http://ppbio.inpa.gov.br/sites/default/files/Estrutura_vegetacao.pdf. For statistical analyzes the total density of plants (sum values from Transects 1, 2 and 3 combined) per plot was used.

SOIL NUTRIENT COMPOSITION. –Soil pH was obtained from the effective H+ ion concentration, determined with a combined electrode directly immersed in a soil solution diluted with distilled water at a 1:2.5ml ratio. Calcium, Magnesium and exchangeable

Aluminum were extracted with KCl 1M. Exchangeable Al+3 was titrated with NaOH 0.025M using bromothymol blue as an indicator. Ca+2 and Mg+2 levels were determined by atomic absorption spectrophotometry (AAS). Potassium and soil micronutrients (iron, zinc and manganese) was extracted with Mehlich I2 extraction solution (double-acid solution), consisting of a mixture of HCl 0.05M + H2SO4 0.0125M. The mL extract ratio was 1:10. K,

Fe, Zn and Mn were determined by AAS. Available phosphorus was determined with a colorimetric spectrophotometer, using 3% ammonium molybdate and ascorbic acid. Using

115

these values, formula was applied to the sum of bases, following the methods of Quesada et al.

(2010), which allowed soil fertility in each plot to be inferred. For statistical analyzes the value for the sum of bases in each plot was used.

SOIL SAND AND CLAY CONTENT. –Soil samples were collected at six points on each plot

(0, 50, 100, 150, 200 e 250 m along the plot length), at depths of 0 and 5 cm, once surface leaves had been removed. Samples were collected with a 5.5 cm diameter manual auger, stored in plastic bags and subsequently dried at room temperature and cleaned with tweezers, removing all pieces of leaf, root and charcoal. The material was processed and screened with a 2mm mesh sieve, then separated from other soil impurities to yield Fine Air-Dried Earth – FADE. Particle size analysis was made with composite samples (mixing sub-samples from soil obtained at 0,

50,100, 150, 200 and 250 m) at INPA’s Soil and Plant Science Laboratory. Particle size was estimated from an aliquot of 10 grams of soil by adding the chemical dispersant sodium pyrophosphate to separate soil particles. Organic matter was oxidized by heating with hydrogen peroxide. The proportion of clay was determined by dry weight of 20 ml of soil suspension.

The coarse fraction (fine and coarse sand) were separated by sieving, dried in an oven (105 ° C for 24 hours) and weighed to obtain the respective percentages, following the PPBio methodology (http://ppbio.inpa.gov.br/knb/metacat). The average percentage of clay in the soil of each plot was used to represent particle size and this was then used in statistical analyzes.

ELEVATION ̶ A professional surveyor measured the elevation above sea level at the starting point of the plot. This was done because, to minimize variation in vegetation, soil type and drainage, each plot follows the local contour line and, consequently, variation in elevation is minimal along its length. The value of the elevation of each plot was used for statistical analysis.

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Literature Cited

Quesada CA, Lloyd J, Schwarz M, Patiño S, Baker RT, Czimczik C et al. Variations in chemical and physical properties of Amazon forest soils in relation to their genesis. Biogeosciences.

2010; 7: 1515–1541. doi: 10.5194/bg-7-1515-2010.

S2 Fig 1.

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S3 Fig 2.

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121

Síntese

A maior parte da biodiversidade mundial está concentrada na região Neotropical, especialmente na região amazônica. No entanto, diversas áreas ainda necessitam ser inventariadas. Sabe-se que dentro do espectro geográfico de ocorrência das espécies, diferentes habitats não são igualmente utilizados. Variáveis estruturais do ambiente, por sua vez, são reconhecidas por interferir na distribuição dos organismos determinando um ótimo ambiental ao longo de um gradiente de distribuição. Essas variáveis são frequentemente representadas por fatores físicos do ambiente que podem ter envolvimento na promoção de processos de especiação ecológica, mesmo com ausência de barreiras visíveis. Para lagartos amazônicos, já havia sido observada a influência de gradientes ambientais em escala local, sendo estes ligados a aspectos florestais, edáficos, de proximidade a corpos d’água, ou mesmo declividade ou altitude do terreno. Dentre os estudos envolvendo lagartos, este foi o primeiro a abranger uma escala tão ampla de uma área intefluvial para a Amazônia brasileira com o objetivo de testar o efeito de fatores estruturais e climáticos do ambiente, além da influência de fatores históricos sobre as assembleias de lagartos em ambientes de florestas de terra firme. Todas as amostragens padronizadas, para os três capítulos, não teriam sido realizadas sem a instalação de módulos de acordo com o método RAPELD de amostragem de biodiversidade. Cada módulo foi composto por duas trilhas principais de 5 km de extensão, paralelas e separadas por 1 km, com distintas parcelas de 250 m localizadas ao longo das trilhas principais. Nossas coletas ocorreram por meio de busca ativa visual limitada por tempo e varredura na liteira. No primeiro capítulo foi realizado o mapeamento da distribuição e abundância dos lagartos presentes nos 10 módulos, localizados ao longo da rodovia BR-319, que corta o Interflúvio Purus-Madeira, e liga as cidades de Manaus (Amazonas) a Porto Velho (Rondônia). Como resultado foram encontrados 25 táxons distribuídos em oito famílias, e observado um padrão bastante heterogêneo de ocorrência e abundância ao longo da área de estudo. Assim, estes resultados ampliam o conhecimento das distribuições de lagartos para esta área de endemismo e proporciona dados que podem ser utilizados como base em estudos ecológicos e de monitoramento dessa paisagem megadiversa e crescentemente ameaçada por mudanças de origem antrópica. No segundo capítulo o objetivo foi testar se fatores climáticos e aspectos estruturais do ambiente estariam a moldar a riqueza, composição e diversidade funcional de assembleias de 122

lagartos em larga-escala na Amazônia. Para isto, foram avaliados 10 módulos instalados ao longo da BR-319, e quatro módulos instalados ao longo da margem oeste do Alto Rio Madeira. Como resultado foram quantificados 26 táxons em 17 gêneros distribuídos em nove famílias, sendo a família Gymnophthalmidae a mais diversa, representada por sete espécies. As assembleias de lagartos foram distintas entre os diferentes tipos de floresta ombrófila: densa e aberta. Além disso o gradiente biogeográfico, representado pelas variáveis ambientais em conjunto, explicou uma alta proporção (86%) da variação na composição de espécies para a região. Entretanto, a riqueza de espécies não foi explicada pelo gradiente biogeográfico, o que sugere que a heterogeneidade ambiental seleciona espécies ao longo da área de estudo, tornando as assembleias distintas ao longo da paisagem amostrada. Quando foram observadas as variáveis ambientais de forma individual, foi verificado que tanto a proporção de argila no solo, quanto a área basal florestal e pluviosidade foram capazes de explicar a variação na composição. Porém, a área basal e a pluviosidade foram capazes de melhor prever, de forma contínua, a mudança na composição das assembleias de lagartos. Em relação à diversidade funcional, diferenças entre os tipos de florestas ombrófilas explicou a riqueza de traços funcionais (FRiq), porém a dissimilaridade dos traços funcionais (FDis) não foi significativamente afetada por esta mudança florestal. O gradiente biogeográfico foi capaz de explicar 35% da variação na riqueza funcional, mas não foi relacionado com a dispersão dos traços funcionais. A riqueza funcional apresentou relação com o gradiente de área basal e com pluviosidade local. As taxas de substituição de traços funcionais foram relativamente baixas ao longo do interflúvio, não sendo explicadas por nenhum dos gradientes ambientais. Assim, um complexo de fatores estruturais e climáticos atuam de forma conjunta sobre o estabelecimento dos lagartos na região do interflúvio Purus-Madeira, influenciando tanto a composição quanto a diversidade funcional das assembleias. No terceiro e último capítulo foram abordados, de forma integrada, o efeito do alto rio Madeira, em escala regional, como possível barreira biogeográfica para as assembleias de lagartos presentes ao longo das margens leste e oeste do rio, e em escala local, a possível influência de variáveis ambientais. A coleta de dados foi realizada em 83 parcelas de 250 metros, as quais foram amostradas em quatro ocasiões distintas. As variáveis ambientais aferidas para testar o efeito de gradientes foram: número de árvores, densidade de arbustos, proporçao de argila e areia, nutrientes do solo, e elevaçao do terreno. Os resultados para as 27 espécies demonstraram que, em escala regional, o alto rio Madeira atua como uma barreira

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biogeográfica para 29,6% das espécies de lagartos, com cinco espécies (18.5%) restritas ao lado oeste, e três espécies (11.11%) restritas ao lado leste da região de estudo. Em relação aos gradientes ambientais, para a margem leste o gradiente de elevação melhor explicou a composição de espécies, e para a margem oeste a estrutura da vegetação foi a variável mais explicativa. Assim, foi demonstrado que tanto fatores históricos regionais quanto fatores ambientais locais moldam as assembleias de lagartos do alto Rio Madeira. De modo geral este estudo, pioneiro em investigar assembleias de lagartos em diferentes escalas espaciais e sob diferentes métricas de diversidade, abre novas perspectivas na biogeografia e na ecologia de comunidades tropicais. E que futuros estudos envolvendo delineamentos amostrais em larga-escala e amostragem de diferentes grupos de organismos deverão colaborar no entendimento dos principais promotores da distribuição heterogênea da megadiversidade amazônica.

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REFERÊNCIAS BIBLIOGRÁFICAS

Aleixo, A. 2006. Historical diversification of floodplain forest specialist species in the Amazon: A case study

with two species of the avian genus Xiphorhynchus (Aves: Dendrocolaptidae). Biological Journal of

the Linnean Society, 89: 383–395.

Aleixo, A. 2009. Knowledge gaps, research priorities, and future perspectives on bird conservation in the

Brazilian Amazon. In: De Luc, A.C.; Devele, P.E.; Benck, G.A.; Goerck, J.M. (Eds). Áreas

importantes para a Conservação das Aves no Brasil. Parte II–Amazônia, Cerrado e Pantanal. Vol. 1.

Save Brasil, São Paulo, SP. p. 59–69.

Almeida, A.P.; Carvalho, V.T.; Gordo, M. 2015. Levantamento da herpetofauna em cinco Unidades de

Conservação na região do Interflúvio Madeira–Purus, Estado do Amazonas. In: Gordo, M.; Santos,

H.P. (Eds). Unidades de Conservação do Amazonas no Interflúvio Purus–Madeira: Diagnóstico

Biológico. Vol. 1. EDUA, Manaus, Amazonas. p. 118–138.

Andrade, S.P.D.; Santos, D.L.; Kawashita–Ribeiro, R.A.; Vaz–Silva, W. 2013. New records and updated

distribution map of Iphisa elegans Gray, 1851 (Reptilia, Gymnophthalmidae). Herpetology Notes, 6:

395–400.

Antonelli, A.; Nylander, J.A.A.; Persson, C.; Sanmartín, I. 2009. Tracing the impact of the Andean uplift on

Neotropical plant evolution. Poceedings of the national academy of sciences, 106: 9749–9754.

Antonelli, A.; Quijada–Mascareñas A.; Crawford, A.J.; Bates, J.M.; Velazco, P.M.; Wüster, W. 2010.

Molecular studies and phylogeography of Amazonian tetrapods and their relation to geological and

climatic models. In: Hoorn, C.; Wesselingh, F.P. (Eds.). Amazonia, landscape and species evolution.

Vol. 1. Blackwell Publishing, Oxford, UK. p. 386–403.

Ávila-Pires, T.C.S. 1995. Lizards of Brazilian Amazonia (Reptilia: Squamata). Zoologische Verhandelingen,

Leiden, USA. 706 pp.

125

Ávila-Pires, T.C.; Mulcahy, D.G.; Werneck, F.P.; Sites-Jr, J.W. 2012. Phylogeography of the teiid lizard

Kentropyx calcarata and the Sphaerodactylid Gonatodes humeralis (Reptilia: Squamata): testing a

geological scenario for the lower Amazon–Tocantins Basins, Amazonia, Brazil. Herpetologica, 68:

272–287.

Ávila-Pires, T.C.S.; Alves–Silva, K.R.; Laís, B.; Correa, F.S.; Consenza, J.F.A.; Costa–Rodrigues, A.P.V.;

Cronemberger, A.A.; Hoogmoed, M.S.; Lima–Filho, G.R.; Maciel,A.O.; Missassi, A.F.R.;

Nascimento, L.R.S.; Nunes, A.L.S.; Oliveira, L.S.; Palheta, G.S.; Pereira Jr, A.J.S.; Pinheiro, L.;

Santos–Costa, M.C.; Pinho, S.R.C.; Silva, F.M.; Silva, M.B.; Sturaro, M.J. 2018. Changes in

amphibian and reptile diversity over time in Parque Estadual do Utinga, a protected area surrounded

by urbanization. Herpetology Notes, 11: 449–512.

Ávila-Pires, T.C.S.; Hoogmoed, M.S. 2000. On two new species of Pseudogonatodes Ruthven, 1915

(Reptilia: Squamata: Gekkonidae), with remarks on the distribution of some other sphaerodactylid

lizards. Zoologische Mededelingen, 73: 209–223.

Ávila-Pires, T.C.S.; Hoogmoed, M.S.; Vitt, L.J. 2007. Herpetofauna da Amazônia. In: Nascimento, L.B.;

Oliveira, M.E (Eds). Herpetologia no Brasil II. Sociedade Brasileira de Herpetologia, Belo Horizonte.

p. 13–43

Ávila-Pires, T.C.S.; Vitt, L.J.; Sartorius, S.S.; Zani, P.A. 2009. Squamata (Reptilia) from four sites in

southern Amazonia, with a biogeographic analysis of Amazonian lizards. Boletim do Museu Paraense

Emílio Goeldi, 4(2): 99–118.

Ayres, J.M.; Clutton–Brock, T.H. 1992. River boundaries and species range size in Amazonian primates.

American Naturalist, 140: 531–537.

Ballinger, R.E. 1979. Intraspecific variation in demography and life history of the lizard, Sceloporus jarrovi,

along an altitudinal gradient in southeastern Arizona. Ecology, 60: 901–909.

Balmford, A.; Whitten, T. 2003. Who should pay for tropical conservation, and how could the costs be met?

Oryx, 37: 238–250.

126

Barlow, J.; Mestre, L.A.M.; Gardner, T.A.; Peres, E.C.A. 2007. Litter fall and decomposition in primary,

secondary and plantation forests in the Brazilian Amazon. Forest Ecology and Management, 247: 91–

97.

Barros, O.G.; Cintra, R. 2009. The effects of forest structure on occurrence and abundance of three owl

species (Aves: Strigidae) in the Central Amazon Forest. Revista Brasileira de Zoologia, 26: 86–95.

Bergallo, H.G.; Rocha, C.F.D. 1993. Activity pattern and body temperature of two sympatric lizards with

different foraging tactics in southeastern Brazil. Amphibia Reptilia, 4: 312–315.

Bergmann, P.J.; Russell, A.P. 2007. Systematics and biogeography of the widespread Neotropical gekkonid

genus Thecadactylus (Squamata), with the description of a new cryptic species. Zoological Journal of

the Linnean Society, 149: 339–370.

Bernanrd, E.; Penna, L.A.O.; Araújo, E. 2014. Downgrading, downsizing, degazettement and reclassification

of protected areas in Brazil. Conservation Biology, 28: 939–950.

Bernarde, P.S.; Macedo, L.C. 2008. Impacto do desmatamento e formação de pastagens sobre a anurofauna

de serapilheira em Rondônia. Iheringia, Sér Zool, 98(4): 454–459.

Bernardi, J.V.E; Lacerda, L.D.; Dórea, J.G.; Landim, P.M.B.; Gomes, J.P.O.; Almeida, R.; Mnzatto, A.G.;

Bastos, W.R. 2012. Aplicação da análise das componentes principais na ordenação dos parâmetros

físicos–químicos no alto Rio Madeira e afluentes, Amazônia Ocidental. Geochim Brasiliensis, 23: 79–

90.

Berriozabal–Islas, C.; Badillo–Saldaña, L.M.; Ramírez–Bautista, A.; Moreno, C.E. 2017. Effects of habitat

disturbance on lizard functional diversity in a tropical dry forest of the Pacific Coast of

Mexico. Tropical Conservation Science, 10: 1–11.

Bezerra, R.B.; Trindade, A.G. 2006. Caracterização de parâmetros pluviométricos, térmicos do balanço

hídrico climatológico e desmatamento de Porto Velho – RO. Geografia, 15(1): 65–80.

Bittencourt, S. 2008. A insularização como agente de fragmentação florestal em comunidades de lagartos

da Amazônia Central. Dissertação de mestrado, Instituto Nacional de Pesquisas da Amazônia, Manaus,

Amazonas. 49pp.

127

Boaratti, A.Z.; Da Silva, F.R. 2015. Relationships between environmental gradients and geographic variation

in the intraspecific body size of three species of frogs (Anura). Austral ecology, 40(8): 869–876.

Bobrowiec, P.E.D.; Tavares, V.D.C. 2017. Establishing baseline biodiversity data prior to hydroelectric dam

construction to monitoring impacts to bats in the Brazilian Amazon. PLoS ONE, 12(9): 1–18.

Bock, B.C.; Ortega, A.M.; Zapata, A.M.; Páez, V.P. 2009. Microgeographic body size variation in a high

elevation Andean anole (Anolis mariarum; Squamata, Polychrotidae). Revista de biologia

tropical, 57(4): 1253–1262.

Böhm, M.; Collen, B.; Baillie, J.E.; Bowles P.; Chanson, J.; Cox, N.; Rhodin, A.G. 2013. The conservation

status of the world’s reptiles. Biological Conservation, 157: 372–385.

Borges, S.H.; Da Silva, J.M. 2012. A new area of endemism for Amazonian birds in the Rio Negro Basin. The

Wilson Journal of Ornithology, 124(1): 15–23.

Boubli, J.P.; Ribas, C.; Alfaro, J.L.; da Silva, M.N.F.; Pinho, G.M.; Farias, I.P. 2014. Spatial and temporal

patterns of diversification on the Amazon: a test of the riverine hypothesis for all diurnal primates of

Rio Negro and Rio Branco in Brazil. Molecular Phylogenetics and Evolution, 82: 400–412.

Brandt, R.; Navas, C.A. 2011. Life–history evolution on Tropidurinae lizards: influence of lineage, body size

and climate. PLoS ONE, 6(5): e20040.

Brattstrom, B.H. 1965. Body temperatures of reptiles. American Midland Naturalist, 2: 376–422.

Brum, T.R.; Santos–Filho, M.; Canale, G.R.; Ignácio, A.R.A. 2018. Effects of roads on the vertebrates

diversity of the Indigenous Territory Paresi and its surrounding. Brazilian Journal of Biology, 78: 125–

132.

Bueno, A.S.; Bruno, R.S.; Pimentel, T.P.; Sanaiotti, T.M.; Magnusson, W.E. 2012. The width of riparian

habitats for understory birds in an Amazonian forest. Ecological Applications, 22(2): 722–734.

Buhrnheim, C.M.; Cox–Fernandes, C. 2003. Structure of fish assemblages in Amazonian Rain–Forest

Streams: Effects of habitats and locality. Copeia, 2: 255–262.

Burger, J., Zappalorti, R.T. 1986. Nest site selection by Pine Snakes, Pituophis melanoleucus, in the New

Jersey Pine Barrens. Copeia, (1): 116–121.

Bush, B.M. 1994. Amazonian speciation: a necessary complex model. Journal of Biogeography, 21: 5–17. 128

Caldwell, J.P.; Vitt, E.L.J. 1999. Dietary asymmetry in leaf litter frogs and lizards in a transitional northern

Amazonian rain forest. Oikos, 84: 383–397.

Camargo, A.; Sinervo, B.; Sites Jr.; J.W. 2010. Lizards as model organisms for linking across space and time.

Annual Review of Ecology. Evolution, and Systematics, 40(1): 677–697.

Campbell, H.W.; Christman, S.P. 1982. Field techniques for herpetofaunal community analysis. In: Scott, N.

J. (Ed). Herpetological Communities: a symposium of the society for study of amphibians and reptiles

and the herpetologist’s league. Vol. 13. Wildlife Research Report, Department of the Interior, Fish and

Wildlife Service, Washington, DC. p. 193–200.

Caputo, M.V.; Soares, E.A.A. 2016. Eustatic and tectonic change effects in the reversion of the

transcontinental Amazon River drainage system. Brazilian Journal of Geology, 46(2): 301–328.

Carvalho, V.T.; Esteves, F.A.D.; Diniz, V.C. 2006. Levantamento da fauna de anfíbios e répteis da região do

rio Copacá – Resex do Baixo Juruá. In: Andrade, P.; Carvalho, V.T.; Oliveira, P.H.G.; Anciães, M.;

Rodrigues, L.; Eler, E. (Eds). Plano de Manejo de Fauna da Resex do Baixo Juruá. Vol. 1. Ibama,

Manaus, Amazonas. p. 57–63.

Cavalcante, M.M.A. 2012. Hidroelétricas do Rio Madeira – RO: território, tecnificação e meio ambiente.

Tese de doutorado, Universidade Federal do Paraná. Curitiba, Paraná. 102pp.

Chalcraft, D.R.; Resetarits Jr, W.J. 2003. Mapping functional similarity of predators on the basis of trait

similarities. The American Naturalist, 162(4): 390–402.

Chown, S.L.; Gaston, K.J.; Robinson, D.H. 2004. Macrophysiology: large–scale patterns in physiological

traits and the ecological implications. Functional Ecology, 18: 159–167.

Cintra, B.B.L., Schietti, J., Emilio, T., Martins, D., Moulatlet, G., Souza, P.2013. Soil physical restrictions

and hydrology regulate stand age and wood biomass turnover rates of Purus–Madeira interfluvial

wetlands in Amazonia. Biogeosciences; 10: 7759–7774.

Cole, E.M.; Bustamante, M.R.; Almeida–Reinoso, D.; Funk, W.C. 2014. Spatial and temporal variation in

population dynamics of Andean frogs: Effects of forest disturbance and evidence for declines. Global

Ecology and Conservation, 1: 60–70.

129

Condit, R.; Pitman, N.; Leigh, E.G.; Chave, J.; Terborgh, J.; Foster, R.B.; Hubbell, S.P. 2002. Beta–diversity

in tropical forest trees. Science, 295(5555): 666–669.

Costa, F.R.C.; Magnusson, W.E.; Luizão, R.C. 2005. Mesoscale distribution patterns of Amazonian

understorey herbs in relation to topography, soil and watersheds. Journal Ecology, 93: 863–878.

Costa, G.C.; Mesquita, D.O.; Colli, G.R.; Vitt, L.J. 2008. Niche expansion and the niche variation hypothesis:

does the degree of individual variation increase in depauperate assemblages?. The American

Naturalist, 172(6): 868–877.

Cracraft, J. 1985. Historical biogeography and patterns of differentiation within the South American

avifauna: areas of endemism. Ornithological Monographs, 36: 49–84.

Cracraft, J.; Prum, R.O. 1988. Pattern and processes of diversification in some Neotropical birds. Evolution,

43: 603–620.

Crump, M.L.; Scott, Jr.N.J. 1994. Visual encounter surveys. In: Heyer, W.R.; Donnelly, M.A.; McDiarmid,

R.W.; Hayek, L.C.; Foster, M.S. (Eds). Measuring and Monitoring Biological Diversity: Standard

Methods for Amphibians. Vol. 2. Smithsonian Institution Press, Washington, USA. p. 84–92.

Dambros, C.S.; Azevedo, R.A.; Gotelli, N.J. 2016. Isolation by distance, not rivers, control the distribution

of termite species in the Amazonian rain forest. Ecography, 39: 1–9.

D'angiolella, A.B.; Gamble, T.; Ávila–Pires, T.C.; Colli, G.R.; Noonan, B.P.; Vitt, L.J. 2011. Anolis

chrysolepis Duméril and Bibron, 1837 (Squamata: Iguanidae), revisited: molecular phylogeny and

taxonomy of the Anolis chrysolepis species group. Bulletin of the Museum of Comparative Zoology,

160: 35–63. da-Silva, J.M.D.; Rylands, A.B.; da Fonseca, G.A.B. 2005. The fate of the Amazonian areas of endemism.

Conservation Biology, 19: 689–694.

Daws, M.; Mullins, C.; Burslem, D.; Paton, S.; Dalling, J. 2002. Topographic position affects the water

regime in a semideciduous tropical forest in Panama. Plant Soil and Environment, 238: 79–90.

De Freitas, M.A.; França, D.P.F.; Veríssimo, D. 2016. First record of Cercosaura eigenmanni (Griffin, 1917)

(Squamata: Gymnophthalmidae) for the state of Acre, Brazil. Check List, 7: 510–516.

130

De-Abreu, F.H.T.; Schietti, J.; Anciães, M. 2018. Spatial and environmental correlates of intraspecific

morphological variation in three species of passerine birds from the Purus–Madeira interfluvium,

Central Amazonia. Evolutionary Ecology, 32: 191–214.

DeFaveri, J.; Jonsson, P.R.; Merilä, J. 2013. Heterogeneous genomic differentiation in marine threespine

sticklebacks: adaptation along an environmental gradient. Evolution, 67(9): 2530–2546.

De-França, D.B.; Galuch, A.V.; Zuanon, J.; Santo, H.M.V.E.; de–Mendonça, F.P.; Albernaz, A.L.M. 2011.

The fish fauna of streams in the Madeira–Purus interfluvial region, Brazilian Amazon. Check List, 7:

768–773.

Dexter, K.G.; Terborgh, J.W.; Cunningham, C.W. 2012. Historical effects on beta diversity and community

assembly in Amazonian trees. Proceedings of the national academy of sciences, 109: 7787–7792.

Dias-Terceiro, R.G.; Kaefer, I.L.; de Fraga, R.; de Araújo, M.C.; Simões, P.I.; Lima, A.P. 2015. A matter of

scale: historical and environmental factors structure anuran assemblages from the Upper Madeira river,

Amazonia. Biotropica, 47: 259–266.

Dixo, M.B.O. 2001. Efeito da fragmentação da floresta sobre a comunidade de sapos e lagartos de

serapilheira no sul da Bahia. Tese de doutorado, Instituto de Biociências da Universidade de São Paulo,

São Paulo, SP. 96pp.

Dobson, F.S.; Michener, G.R. 1995. Maternal traits and reproduction in Richardson's ground

squirrels. Ecology, 76(3): 851–862.

Driscoll, D.A. 2004. Extinction and outbreaks accompany fragmentation of a reptile community. Ecol Appl,

14: 220–240.

Drucker, D.P.; Costa, F.R.C.; Magnusson, W.E. 2008. How wide is the riparian zone of small streams in

tropical forests? A test with terrestrial herbs. Journal Tropical Ecolology, 24: 65–74.

Elith, J.; Leathwick, J.R. 2009. Species distribution models: ecological explanation and prediction across

space and time. Annual review of ecology, evolution, and Systematics, 40: 677–697.

Emilio, T.; Quesada, C.A.; Costa, F.R.C.; Magnusson, W.E.; Schietti, J.; Feldpausch, T.R. 2013. Soil

physical conditions limit palm and tree basal area in Amazonian forests. Plant Ecology and Diversity,

7: 215–229. 131

Endler, J.A. 1977. Geographic Variation, Speciation, and Clines. Princeton: Princeton University Press.

Esther, M.; Cole, G.; Bustamanteb, M.R.; Almeida–Reinoso, D.; Chris Funk, W. 2014. Spatial and temporal

variation in population dynamics of Andean frogs: Effects of forest disturbance and evidence for

declines. Global Ecology and Conservation, 1: 60–70.

Faria, A.S.; Menin, M.; Kaefer, I.L. 2019. Riparian zone as a main determinant of the structure of lizard

assemblages in upland Amazonian forests. Austral Ecolology, 1: 1–9.

Fauth, J.F.; Crother, B.I.; Slowinski, E.J.B. 1989. Elevational patterns of species richness, evenness, and

abundance of the Costa Rican leaf–litter herpetofauna. Biotropica, 21: 178–185.

Fearnside, M.P. 2014. Brazil's Madeira River dams: A setback for environmental policy in Amazonian

development. Water Alternative, 7: 256–269.

Fearnside, P.M. 2006. Desmatamento na Amazônia: dinâmica, impactos e controle. Acta Amazônica, 36(3):

395–400.

Fearnside, P.M.; Graça, P.; Keizer, E.H.; Maldonado, F.D.; Barbosa, R.I.; Nogueira, E.M. 2009. Modelagem

de desmatamento e emissões de gases de efeito estufa na região sob influência da rodovia Manaus–

Porto Velho (BR–319). Revista Brasileira de Meteorologia, 24: 208–233.

Fearnside, P.M.; Graça, P.M.L.A. 2006. BR–319: Brazil’s Manaus–Porto Velho Highway and the potential

impact of linking the arc of deforestation to central Amazonia. Environmental Management, 38(5):

705–716.

Fernandes, A.M.; Gonzalez, J.; Wink, M.; Aleixo, A. 2013. Multilocus phylogeography of the Wedge–billed

Woodcreeper Glyphorynchus spirurus (Aves, Furnariidae) in lowland Amazonia: Widespread cryptic

diversity and paraphyly reveal a complex diversification pattern. Molecular Phylogenetics and

Evolution, 66(1): 270–282.

Ferrão, M.; Colatreli, O.; Fraga, R.; Kaefer, I.L.; Moravec, J.; Lima, A.P. 2016. High species richness of

Scinax treefrogs (Hylidae) in a threatened landscape revealed by an integrative approach. PLoS ONE,

11: 1–16.

Ferrão, M.; Moravec, J.; Fraga, R.; Almeida, A.P.; Kaefer, I.L.; Lima, A.P. 2017. A new species of Scinax

from the Purus–Madeira interfluve, Brazilian Amazonia (Anura, Hylidae). ZooKeys, 706: 137–162. 132

Fine, P.V.A; Zapata, F.; Daly, D.C. 2014. Investigating processes of neotropical rain forest tree

diversification by examining the evolution and historical Biogeography of the Protieae (burseraceae).

Evolution, 6: 1–17.

Fischer, J.; Lindenmayer, D.B. 2005. The sensitivity of lizards to elevation: A case study from south-eastern

Australia. Divers Distrib, 11: 225–233.

Fouquet, A.; Courtois, E.A.; Baudain, D.; Lima, J.D.; Souza, S.M.; Noonan, D.P.; Rodrigues, M.T. 2015.

The trans–riverine genetic structure of 28 Amazonian frog species is dependent on life history. Journal

Tropical Ecology, 31: 361–373.

Fraga, R.D.; Stow, A.J.; Magnusson, W.E.; Lima, A.P. 2014. The Costs of Evaluating Species Densities and

Composition of Snakes to Assess Development. Impacts in Amazonia. PLoS ONE, 9(8): 1–9.

Fraga, R.de.; Ferrão, M.; Stow, A.J.; Magnusson, W.E.; Lima, A.P. 2018. Different environmental gradients

affect different measures of snake β–diversity in the Amazon rainforests. PeerJ, 6: 1–22.

Fraga, R.de.; Lima, A.P.; Magnusson, W.E. 2011. Mesoscale spatial ecology of a tropic snake assemblage:

the width of riparian corridors in central Amazonia. Herpetologica Journal 21: 51–57.

Fraga, R.de.; Lima, A.P.; Magnusson, W.E.; Ferrão, M.; Stow, A.J. 2017. Contrasting patterns of gene flow

for Amazonian snakes that actively forage and those that wait in ambush. Journal of Heredity, 108(5):

524–534.

Franklin, E.; Magnusson, W.E.; Luizão, F.J. 2005. Relative effects of biotic and abiotic factors on the

composition of soil invertebrates’ communities in an Amazonian savannah. Applied Soil Ecology, 29:

259–273.

Fraterrigo, J.M.; Wagner, S.; Warren, R.J. 2004. Local–scale biotic interactions embedded in macroscale

climate drivers suggest Eltonian noise hypothesis distribution patterns for aninvasive grass. Ecology

Letters, 17(11): 1447–1454.

Garda, A.A.; Wiederhecker, H.C.; Gainsbury, A.M.; Costa, G.C.; Pyron, R.A.; Vieira, G.H.C.; Werneck,

F.P.; Colli, E.G.R. 2013. Microhabitat variation explains local–scale distribution of terrestrial

Amazonian Lizards in Rondônia, Western Brazil. Biotropica, 45: 245–252.

133

Gardner, T.A.; Barlow, J.; Araujo, I.S.; Ávila–Pires, T.C.; Bonaldo, A.B. 2008. The cost–effectiveness of

biodiversity surveys in tropical forests. Ecology Letters, 11: 139–150.

Gascon, C., Lougheed, S.C.; Bogart, J.P. 1996. Genetic and morphological variation in Vanzolinius

discodactylus: a test of the river hypothesis of speciation. Biotropica, 28: 376–387.

Gascon, C.; Malcolm, J.R.; Patton, J.L.; Silva, M.N.F.; Bogart, J.P.; Lougheed, S.C.; Peres, C.A.; Neckel,

S.; Boag, P. 2000. Riverine barriers in the geographic distribution of Amazonian species. Proceedings

of the National Academy of Sciences, 97: 13672–13677.

Gaston, K.J.; Blackburn, T.M. 2003. Macroecology and conservation biology. In: Blackburn, T.M.; Gaston,

K.J. (Eds). Macroecology: Concepts and consequences., Vol. 1. Blackwell Science, Oxford. p. 345–

367.

Gentry, A.H. 1988. Changes in plant community diversity and floristic composition on environmental and

geographical gradients. Ann Mo Bot Gard, 75: 1–34.

Geurgas, S.R.; Rodrigues, M.T. 2010. The hidden diversity of Coleodactylus amazonicus

(Sphaerodactylinae, Gekkota) revealed by molecular data. Molecular Phylogenetics and Evolution, 54:

583–593.

Gibbs, H.L.; Sovic, M.; Amazonas, D.; Chalkidis, H.; Salazar–Valenzuela, D.; Moura–Da–Silva, A.M. 2018.

Recent lineage diversification in a venomous snake through dispersal across the Amazon River. Biol J

Linn Soc Lond, 123(3): 651–665.

Godinho, M.B.C; Da Silva, F.R. 2018. The influence of riverine barriers, climate, and topography on the

biogeographic regionalization of Amazonian anurans. Scientific Reports, 8: 3427.

Guisan, A.; Hofer, U. 2003. Predicting reptile distributions at the mesoscale: relation to climate and

topography. Journal of Biogeography, 30(8): 1233–1243.

Hadden, S.A.; Westbrooke, M.E. 1996. Habitat relationships of the herpetofauna of remnant buloke

woodlands of the Wimmera Plains, Victoria. Wildlife Research, 23(3): 363–372.

Haffer, J. 1969. Speciation in Amazonian forest birds. Science, 165: 131–137.

Haffer, J. R. 1997. Alternative models of vertebrate speciation in Amazonia: an overview. Biodiversity &

Conservation, 6: 451–476. 134

Hangartner, S., Laurila, A., Räsänen, K. 2012. Adaptive divergence in moor frog (Rana arvalis) populations

along an acidification gradient: inferences from QST–FST correlations. Evolution Letters, 66(3): 867–

881.

Haseyama, K.L.F.; Carvalho, C.J.B. 2011. Distributional patterns of amazon biodiversity: an evolutionary

point of view. Revista da Biologia, 2: 35–40.

Haugaasen, T.; Peres, C.A. 2005. Mammal assemblage structure in Amazonian floodedand unflooded

forests. Journal Tropical Ecolology, 2: 133–145.

Hayes, F.E.; Sewlal, J.N. 2004. The Amazon River as a dispersal barrier to passerine birds: effects of river

width, habitat and taxonomy. Journal of Biogeography, 31: 1809–1818.

Hijmans, R.J.; Cameron, S.E.; Parra, J.L.; Jones, P.G.; Jarvis, A. 2005. Very high resolution interpolated

climate surfaces for global land areas. International Journal of Climatology, 25(15): 1965–1978.

Hobbs, R.J.; Higgs, E.; Harris, J.A. 2009. Novel ecosystems: implications for conservation and

restoration. Trends in ecology & evolution, 24(11): 599–605.

Hoogmoed, M.S.; Ávila–Pires, T.C. 1992. Studies on the species of the South American lizard genus

Arthrosaura Boulenger (Reptilia: Sauria: Teiidae), with the resurrection of two species. Zoologische

Mededeelingen, 66(35): 453–484.

Hoorn, C.; Wesselingh, F.P.; Ter Steege, H.; Bermudez, M.A.; Mora, A.; Sevink, J.; Antonelli, A. 2010.

Amazonia through time: Andean uplift, climate change, landscape evolution, and

biodiversity. Science, 330(6006): 927–931.

Hoorn, C.; Wessenligh, F. 2010. Introduction. In: Hoorn, C.; Wesseling, F. (Eds). Amazonia: landscape and

species evolution, a look into the past. Vol. 1. Blackwell Publishing, Oxford, UK. p. 386–404.

Huey, R.B.; Slatkin, M. 1976. Costs and benefits of lizard thermoregulation. Quarterly Review of Biology,

51: 363–384.

Hurvich, C.M.; Tsai, C.L. 1989. Regression and time series model selection in small

samples. Biometrics, 76(2): 297–307.

IBGE. 1997. Instituto Brasileiro de Geografia e Estatística. Recursos naturais e meio ambiente: uma visão

do Brasil. Rio de Janeiro. 135

INPE. 2016. Projeto DETER–B. Instituto Nacional de Pesquisas

Espaciais.(http://www.inpe.br/cra/projetos_pesquisas/deterb.php). Acesso: 20/10/16.

James, C.; Shine, R. 1988. Life–history strategies of Australian lizards: a comparison between the tropics

and the temperate zone. Oecologia, 75(2): 307–316.

Juen, L.; De Marco, P. 2012. Dragonfly endemism in the Brazilian Amazon: competing hypotheses for

biogeographical patterns. Biodiversity and Conservation, 21(13): 3507–3521.

Kaefer, I.L.; Tsuji–Nishikido, B.M.; Mota, E.P.; Farias, I.P.; Lima, A.P. 2013. The early stages of speciation

in Amazonian forest frogs: phenotypic conservatism despite strong genetic structure. Evol Biol, 40:

228–245.

Karr, J.R.; Freemark, K.E. 1983. Habitat selection and environmental gradients: dynamics in the" stable"

tropics. Ecology, 64(6): 1481–1494.

Kinupp, V.F.; Magnusson, W.E. 2005. Spatial patterns in the understorey shrub genus Psychotria in central

Amazonia: effects of distance and topography. Journal Tropical Ecology, 21: 363–374.

Kraft, N.J.B.; Adler, P.B.; Godoy, O.; James, E.C.; Fuller, S.; Levine, J.M. 2014. Community assembly,

coexistence and the environmental metaphor. Functional Ecolology, 29: 592–599.

Laird, N.M.; Ware, J.H. 1982. Random–effects models for longitudinal data. Biometrics, 38: 963–974.

Laliberté, E.; Legendre, P.; Shipley, B.; Laliberté, M. E. 2014. Package ‘FD’. Measuring functional diversity

from multiple traits, and other tools for functional ecology.

Laurance, W.F.; Balmford, A. 2013. A global map for road building: roads are proliferating across the planet.

Located and designed wisely, they can help rather than harm the environment. Nature, 495: 308–310.

Leite, R.N.; Rogers, D.S. 2013. Revisiting Amazonian phylogeography: insights into diversification

hypotheses and novel perspectives. Organisms Diversity & Evolution, 13(4): 639–664.

Lieberman, S.S. 1986. Ecology of a leaf litter herpetofauna of a neotropical rain litter in functioning of forest

ecosystems. Biological Reviews, 81: 1–31.

Lima, A.P.; Keller, C.; Rebelo, G.H. 2004. Estudos ambientais no Rio Madeira, trecho Cachoeira de Santo

Antônio–Abunã (Rondônia): Herpetofauna. Relatório elaborado para Furnas Centrais Elétricas S.A.

como parte do Estudo de Viabilidade dos AHEs Santo Antônio e Jirau, para o Aproveitamento 136

Hidrelétrico do Rio Madeira. INPA, Manaus.

(http://philip.inpa.gov.br/publ_livres/Dossie/Mad/Documentos%20Oficiais/Madeira_COBRAPE/111

18–COBRAP–report.pdf.). Acesso:10/10/17.

Lobão, P.S.P. 2008. Associações no uso do habitat por cinco espécies de lagartos amazônicos. Dissertaçao

de mestrado, Instituto Nacional de Pesquisas da Amazônia, Manaus, Amazonas. 46pp.

Losos, J.B.; Arnold, S.J.; Bejerano, G.; Brodie, I.E.D.; Hibbett, D.; Hoekstra, H.E.; Mindell, D.P.; Monteiro,

A.; Moritz, C.; Allen Or, H.; Petrov, D.A.; Renner, S.A.; Ricklefs, R.E.; Soltis, P.S.; Turner, T.L. 2013.

Evolutionary biology for the 21st century. PLoS Biology, 11: 1–10.

Magalhães-Silva, F.; Menks, A.C.; Prudente, A.L.C.; Costa, J.C.L.; Travassos, A.E.M.; Gallatti, U. 2011.

Squamate Reptiles from municipality of Barcarena and surroundings, state of Pará, north of Brazil.

Check List, 7: 220–226.

Magnusson, W.E.; Grelle, C.E.V.; Marques, M.C.M.; Rocha, C.F.D.; Dias, B.; Fontana, C.S.; et al. 2018.

Effects of brazil's political crisis on the science needed for biodiversity conservation. Frontiers Ecology

and Evolution, 6: 150–163.

Magnusson, W.E.; Ishikawa, N.K.; Lima, A.P.; Dias, D.V.; Costa, F.M.; de Holanda, A.S.S. et al. 2016. A

linha de véu: a biodiversidade brasileira desconhecida. Parcerias Estratégicas, 21: 45–60.

Magnusson, W.E.; Lima, A.P.; Luizão, R.; Luizão, F.; Costa, F.R.C.; Castilho, C.V.; Kinupp, V.F. 2005.

RAPELD: a modification of the Gentry method for biodiversity surveys in long–term ecological

research sites. Biota Neotropica 5(2): 1–6.

Magnusson, W.E.; Pezzini, R.B.N.; Baccaro, F.F.; Bergallo, F.; Penha, H.; Rodrigues, J.; Verdade, D.J.;

Martins, L.L.; Albernaz, A.; Hero, A.L.; Lawson, J.M.B.; Castilho, E.; Drucker, C.; Franklin, D.;

Mendonça, E.; Costa, F.; Galdino, F.; Guyer, G.; Zuanon, C.; Vale, J.; Santos, J.; Luizão, J.L.C.; Cintra,

R.C.; Barbosa, R.I.; Lisboa, R.; Koblitz, A.; Cunha, R.V.; Pontes, C.N.; Mendes, A.R. 2013.

Biodiversidade e Monitoramento Ambiental Integrado: o sistema RAPELD na Amazônia. Vol. 1.

Publisher Attema, Santo André, SP. 335pp.

Mahecha, M.D.; Schmidtlein, S. 2008. Revealing biogeographical patterns by nonlinear ordinations and

derived anisotropic spatial filters. Global Ecology and Biogeography, 17(2): 284–296. 137

Maia, G.F.; Lima, A.P.; Kaefer, I.L. 2017. Not just the river: genes, shapes, and sounds reveal population–

structured diversification in the Amazonian frog Allobates tapajos (Dendrobatoidea). Biological

Journal of Linnean Society of London, 121: 95–108.

Maldonado, F.D.; Keizer, E.W.H.; Graça, P.M.L.A.; Fearnside, P.M.; Vitel, C.S. 2012. Previsão temporal da

distribuição espacial do desmatamento no Interflúvio Purus–Madeira até o ano 2050. In: Sousa–Junior,

W.C.; Waichman, A.V.; Sinisgalli, P.A.A.; de Angelis, C.F.; Romeiro, A.R. (Eds). Rio Purus: Água,

Território e Sociedade na Amazônia Sul–Ocidental. Vol. 1. LibriMundi, Goiás, Brasil. p. 270–282 p.

Marciente, R.; Bobrowiec, P.E.D.; Magnusson, W.E. 2015. Ground–vegetation clutter affects phyllostomid

bat assemblage structure in lowland Amazonian forest. PLoS ONE, 10: 1–16.

Mariac, C.; Jehin, L; Saïdou, A.A.; Thuillet, A.C.; Couderc, M.; Sire, P., 2011. Genetic basis of pearl millet

adaptation along an environmental gradient investigated by a combination of genome scan and

association mapping. Molecular Ecology, 20(1): 80–91.

Melo-Sampaio, P.R.; Oliveira, R.M.; Prates, I. 2018. A new nurse frog from Brazil (Aromobatidae:

Allobates), with data on the distribution and phenotypic variation of western Amazonian species. South

American Journal of Herpetology, 13: 131–149.

Menger, J.; Magnusson, W.E.; Anderson, M.J.; Schlege, M.; Pe'er, G.; Henle, K. 2017. Environmental

characteristics drive variation in Amazonian understorey bird assemblages. PLoS ONE, 2(2): 1–17.

Menin, M.; Waldez, F.; Lima. A.P. 2011. Effects of environmental and spatial factors on the distribution of

anuran species with aquatic reproduction in central Amazonia. Herpetology Journal, 21: 255–261.

Moraes, L.F.P.D. 2008. Diversidade beta em comunidades de lagartos em duas ecorregiões distintas na

Amazônia. Dissertação mestrado, Programa de pós-graduação em biologia tropical e recursos naturais

da Amazônia. 40pp.

Moraes, L.J.; Pavan, D.; Barros, M.C.; Ribas, C.C. 2016. The combined influence of riverine barriers and

flooding gradients on biogeographical patterns for amphibians and squamates in south‐eastern

Amazonia. Journal of Biogeography, 43(11): 2113–2124.

Moulatlet, G.M.; Costa, F.R.; Rennó, C.D.; Emilio, T.; Schietti, J. 2014. Local hydrological conditions

explain floristic composition in lowland Amazonian forests. Biotropica, 46: 95–03. 138

Murphy, J.C.; Jowers, M.J. 2013. Treerunners, cryptic lizards of the Plica plica group (Squamata, Sauria,

Tropiduridae) of northern South America. ZooKeys, 355: 49–77.

Murphy, J.C.; Jowers, M.J.; Lehtinen, R.M.; Charles, S.P.; Colli, G.R.; Peres Jr, A.K. 2016. Cryptic,

sympatric diversity in Tegu lizards of the Tupinambis teguixin group (Squamata, Sauria, Teiidae) and

the description of three new species. PLoS ONE, 11: 1–15.

Naeem, S. 1998. Species redundancy and ecosystem reliability. Conservation Biology, 12: 39–45.

Naiman, R.J.; Decamps, H.; Pollock, M. 1993. The roles of riparian corridors in maintaining regional

biodiversity. Ecology Application, 3: 209–212.

Nobre, C.A. 2002. Amazônia e o carbono atmosférico. Scientific American Brasil, 6: 36–39.

Oksanen, J.; Blanchet, F.G.; Friendly, M.; Kindt, R.; Legendre, P.; McGlinn, D. 2010. Vegan: Community

Ecology Package. R package version 1.17–1.

Oliveira, D.P.; Carvalho, V.T.; Hrbek, T. 2016. Cryptic diversity in the lizard genus Plica (Squamata):

phylogenetic diversity and Amazonian biogeography. Zoologica Scripta, 45: 630–641.

Ortega, Z.; Pérez–Mellado. 2016. Seasonal patterns of body temperature and microhabitat selection in a

lacertid lizard. Acta Oecologica, 77: 201–206.

Ortiz, D.A.; Lima, A.P.; Werneck, F.P. 2018. Environmental transition zone and rivers shape intraspecific

population structure and genetic diversity of an Amazonian rain forest tree frog. Evolutionary Ecology,

32: 359–378.

Pansonato, M.P.; Costa, F.R.C.; Castilho, C.V.; Zuquim, G. 2013. Spatial scale or amplitude of predictors as

determinants of the relative importance of environmental factors to plant community structure.

Biotropica, 45: 299–307.

Patton, J.L.; da Silva, M.N.F. 1994. Malcolm JR. Gene genealogy and differentiation among arboreal spiny

rats (Rodentia: Echimyidae) of the Amazon Basin: a test of the riverine barrier hypothesis. Evolution

Letters, 48: 1314–1323.

Pavan, S.E.; Jansa, S.A.; Vos, S.R. 2016. Spatiotemporal diversification of a low–vagility Neotropical

vertebrate clade (short–tailed opossums, Didelphidae: Monodelphis). Journal of Biogeography, 43:

1299–1309. 139

Pavoine, S.; Vallet, J.; Dufour, A.B.; Gachet, S.; Daniel, H. 2009. On the challenge of treating various types

of variables: application for improving the measurement of functional diversity. Oikos, 118(3): 391–

402.

Pavoine, S.; Vela, E.; Gachet, S.; Be Lair, G.; Bonsall, M.B. 2011. Linking patterns in phylogeny, traits,

abiotic variables and space: a novel approach to linking environmental filtering and plant community

assembly. Journal of Ecology, 99: 165–175.

Peloso, P.L.V.; Pellegrino, K.C.M.; Rodrigues, M.T.; Ávila–Pires, T.C.S. 2011. Description and

Phylogenetic Relationships of a New Genus and Species of Lizard (Squamata, Gymnophthalmidae)

from the Amazonian Rainforest of Northern Brazil. American Museum Novitates, 37(13): 1–24.

Petchey, O.L.; Evans, K.L.; Fishburn, I.S.; Gaston, K.J. 2007. Low functional diversity and no redundancy

in British avian assemblages. Journal Animal Ecolology, 76: 977–988.

Petchey, O.L.; Gaston, K.J. 2002. Functional Diversity (FD), species richness, and community. Ecology

Letters, 5(3): 402–411.

Petchey, O.L.; Gaston, K.J. 2006. Functional diversity: back to basics and looking forward. Ecology Letters,

9: 741–758.

Peters, J.A.; Donoso–Barros, R. 1970. Lizards and amphisbaenians. In: Peters, J.A.; Donoso–Barros, R.

(Eds). Catalogue of the Neotropical Squamata pt: II. Vol. 4. Bulletin of the United States National

Museum Washington, USA. p. 1–293.

Pianka, E.R. 1986. Ecology and Natural History of Desert Lizards: analyses of the ecological niche and

community structure. Princeton. Princeton University Press. 208 p.

Pinto, M.G.M. 2006. Diversidade Beta, métodos de amostragem e influência de fatores ambientais sobre uma

comunidade de lagartos na Amazônia Central. Tese de Doutorado, Instituto Nacional de Pesquisas da

Amazônia, Manaus, Amazonas. 90pp.

Polis, G.A.; Strong, D.R. 1996. Food Web Complexity and Community Dynamics. The American Naturalist,

147(5): 813–846.

140

Pomara, L.Y.; Ruokolainen, K.; Young, K.R. 2014. Avian species composition across the Amazon River:

the roles of dispersal limitation and environmental heterogeneity. Journal of Biogeography, 41: 784–

796.

Pontes-da-Silva, E.; Magnusson, W.E.; Sinervo, B.; Caetano, G.H.; Miles, D.B.; Colli, G.R.; Werneck, F.P.

2018. Extinction risks forced by climatic change and intraspecific variation in the thermal physiology

of a tropical lizard. Journal of thermal biology, 73: 50–60.

Powney, G.D.; Grenyer, R.; Orme, C.D.L.; Owens, I.P.F.; Meiri, S. 2010. Hot, dry and different: Australian

lizard richness is unlike that of mammals, amphibians and birds. Global Ecology and

Biogeography, 19(3): 386–396.

Pringle, R.M.; Webb, J.K.; Shine, R. 2003. Canopy structure, microclimate, and habitat selection by a

nocturnal snake, Hoplocephalus bungaroides. Ecology, 84(10): 2668–2679.

Prudente, A.L.C.; Magalhães, F.; Menks, A.; Sarmento, J.F.M. 2013. Checklist of Lizards of the Juruti, state

of Pará, Brazil. Check List, 9: 42–50.

Quintero, I.; Keil, P.; Jetz, W.; Crawford, F.W. 2015.Historical Biogeography Using Species Geographical

Ranges. Systematic Biology Advance, 0(0):1–15.

R-Core Team. R. 2019. A language and environment for statistical computing. Vienna, Austria: R Foundation

for Statistical Computing. (https://cran.r–project.org/doc/manuals/r–release/fullrefman.pdf. cited 2

March 2019.).

Racheli, L.; Racheli, T. 2004. Patterns of Amazoniaan areas relationship based on raw distribution of

papilionid butterflies (Lepidoptera: Papilioninae). Biological Journal of the Linnean Society, 82: 345–

357.

Resetarits, W.J.; Chalcraft, D.R. 2007. Functional diversity within a morphologically conservative genus of

predators: implications for functional equivalence and redundancy in ecological

communities. Functional Ecology, 21(4): 793–804.

Ribas, C.C.; Aleixo, A.; Nogueira, A.C.R.; Miyaki, C.Y.; Cracraft, J. 2012. A palaeobiogeographic model

for biotic diversification within Amazonia over the past three million years. Proceedings of the Royal

Society, Biological Sciences, 279: 681–689. 141

Ribas, C.C.; Miyaki, C.Y. 2004. Molecular systematics in Aratinga parakeets: species limits and historical

biogeography in the ‘solstitialis’ group, and the systematic position of Nandayus nenday. Molecular

Phylogenetics and Evolution, 30: 663–675.

Ribeiro-Jr, J.W.; Lima, A.P.; Magnusson, W.E. 2012. The effect of Riparian Zones on species diversity of

frogs in Amazonian Forests. Copeia. 3: 375–381.

Ribeiro-Júnior, M.A. 2015. Catalogue of distribution of lizards (Reptilia: Squamata) from the Brazilian

Amazonia. I. Dactyloidae, Hoplocercidae, Iguanidae, Leiosauridae, Polychrotidae, Tropiduridae.

Zootaxa, 3983: 001–110.

Ribeiro-Junior, M.A.; Amaral, S. 2016 Diversity, distribution, and conservation of lizards (Reptilia:

Squamata) in the Brazilian Amazonia. Neotropical Biodiversity, 2: 195–421.

Richardson, J.L. 2012. Divergent landscape effects on population connectivity in two co-occurring

amphibian species. Mol Ecol, 21: 4437–4451.

Ricklefs, R.E.; Schluter, D. 1993. Species diversity in ecological communities: historical and geographical

perspectives. University of Chicago Press, 414pp.

Rocha, C.F.D. 1994. Introdução à ecologia de lagartos brasileiros. In: Nascimento, L.B.; Bernerdes, A.T.;

Cotta, G.A. (Eds). Herpetologia no Brasil. Vol. 1. Fundação biodiversidade and Fundação Ezequiel

Dias, PUCMG, Minas Geirais, BR. p. 1–68.

Roddaz, M.; Hermoza, W.; Mora, A.; Baby, P.; Parra, M.; Christophoul, F.; Brusset, S.; Espurt, N. 2010.

Cenozoic sedimentary evolution of the Amazonian foreland basin system. In: Hoorn, C.; Wesseling,

F. (Eds). Amazonia: landscape and species evolution, a look into the past. Willey–Blackwell, Oxford.

p. 61–88.

Rodrigues, M.T.; Ávila–Pires, T.C.S. 2005. New lizard of the genus Leposoma (Squamata,

Gymnophthalmidae) from the lower Rio Negro, Amazonas, Brazil. Journal of Herpetology, 39(4): 541

– 546.

Rodrigues, G. B. F. 2014. Padrões de diversidade (riqueza, filogenética e funcional) de quelônios continentais

da América do Sul, seus processos geradores e suas consequências para a conservação. Dissetetaçao

de mestrado. Universidade de Brasília, Brasília. 89pp. 142

Rojas-Ahumada, D.P.; Landeiro, V.L.; Menin, M. 2012. Role of environmental and spatial processes in

structuring anuran communities across a tropical rain forest. Austral Ecolology, 37: 865–873.

Roll, U.; Feldman, A.; Novosolov, M.; Allison, A.; Bauer, A.M.; Bernard, R.; Colli, G.R. 2017. The global

distribution of tetrapods reveals a need for targeted reptile conservation. Nature Ecology &

Evolution, 1(11), 1666–1677.

Ron, S. 2000. Biogeographic area relationships of lowland Neotropical rainforest based on raw distributions

of vertebrate groups. Biological Journal of Linnean Society, 71: 379–402.

Rossetti, D.F. 2014. The role of tectonics in the late Quaternary evolution of Brazil’s Amazonian landscape.

Earth Science Reviews, 139: 362–389.

Rutschmann, A., Miles, D. B., Le Galliard, J. F., Richard, M., Moulherat, S., Sinervo, B., & Clobert, J.

(2016). Climate and habitat interact to shape the thermal reaction norms of breeding phenology across

lizard populations. Journal of Animal Ecology, 85(2), 457–466.

Santorelli, Jr.S.; Magnusson, W.E.; Deus, C.P. 2018. Most species are not limited by an Amazonian river

postulated to be a border between endemism areas. Scientific reports, 2294(8): 1–8.

Santos, E.S., Maia, R.; Macedo, R.H. 2009. Condition–dependent resource value affects male–male

competition in the blue black grassquit. Behavioral Ecology, 20(3): 553–559.

Schietti, J.; Emilio, T.; Rennó, C.D.; Drucker, D.P.; Costa, F.R.; Nogueira, A. 2014. Vertical distance from

drainage drives floristic composition changes in an Amazonian rainforest. Plant Ecology & Diversity,

7: 241–253.

Schietti, J.; Martins, D.; Emilio, T.; Souza, P.F.; Levis, C.; Baccaro, F.B. 2016. Forest structure along a 600

km transect of natural disturbances and seasonality gradients in central–southern Amazonia. Journal

of Ecolology, 104(5): 1335–1346.

Schneider, D.C. 2001. The rise of the concept of scale in ecology. Bioscience, 51(7): 545 556.

Schoener, T.W. 1974. Resource partitioning in ecological communities. Science, 185(4145): 27–39.

Silva, J.M.C.; Rylands, A.B.; Fonseca, G.A.B. 2005. The fate of the Amazonian areas of endemism.

Conservation Biolology, 19: 689–694.

143

Silva, V.N.; Araújo, A.F.B. 2008. Ecologia dos lagartos brasileiros. Technical Books Editora, Rio de

Janeiro, BR. 271pp.

Simões, P.I.; Lima, A.P.; Magnusson, W.E. 2008. Acoustic and morphological differentiation in the frog

Allobates femoralis: Relationships with the upper Madeira river and other potential geological barriers.

Biotropica, 2008; 40: 607–614.

Smith, A.L.; Bull, C.M.; Gardner, M.G.; Driscoll, D.A. 2014. Life history influences how fire affects genetic

diversity in two lizard species. Molecular Ecology, 23: 2428–2441.

Smith, B.T.; McCormack, J.E.; Cuervo, A.M.; Hickerson, M.J.; Aleixo, A.; Cadena, C.D.; Pérez–Emán, J.;

Burney, C.W.; Xie, X.; Harvey, M.G.; Faircloth, B.C.; Glenn, T.C.; Derryberry, E.P.; Prejean, J.;

Fields, S.; Brumfield, R.T. 2014. The drivers of tropical speciation. Nature, 515: 406–409.

Sombroek, W.G. 2000. Amazon landforms and soils in relation to biological diversity. Acta Amazonica, 30:

81–100.

Souza, J.L.P.; Moura, C.A.R.; Harada, A.Y.; Franklin, E. 2007. Diversidade de espécies dos gêneros

Crematogaster, Gnamptogenys e Pachycondyla (Hymenoptera: Formicidae) e complementaridade dos

métodos de coleta durante a estação seca numa estação ecológica do estado do Pará, Brasil. Acta

Amazonica, 37(4): 649–656.

Souza, S.M.; Rodrigues, M.T.; Cohn–Haft, M. 2013. Are Amazonia rivers biogeographic barriers for lizards?

A study on the geographic variation of the spectacled lizard Leposoma osvaldoi Ávila–Pires

(Squamata, Gymnophthalmidae). Journal of Herpetology, 47(3): 511–519.

Souza, V.M.; Souza, M.B.; Morato, E.F. 2008. Efeitos da sucessão florestal sobre a anurofauna (Amphibia:

Anura) da Reserva Catuaba e seu entorno, Acre, Amazônia Sul – Ocidental. Revista Brasileira de

Zoologia, 25: 49–57.

Souza–Filho, P.W.M.; Quadros, M.L.E.S.; Scandolara, J.E.; da Silva–Filho, E.P.; Reis, M.R. 1999.

Compartimentação morfoestrutural e neotectônica do sistema fluvial Guaporé–Mamoré–alto Madeira,

Rondônia–Brasil. Brazilian Journal Geology, 29: 469–476.

144

Strauß, A.; Reeve, E.; Randrianiaina, R.D.; Vences, M.; Glos, J. 2010. The world’s richest tadpole

communities show functional redundancy and low functional diversity: ecological data on

Madagascar's stream–dwelling amphibian larvae. Ecology, 12: 1–10.

Sturaro, M.J; Rodrigues, M.T; Colli, G.R.; Knowles, L.L.; Avila-Pires, T.C.S. 2018. Integrative taxonomy

of the lizards Cercosaura ocellata species complex (Reptilia: Gymnophthalmidae), Zoologischer

Anzeiger, 18: 1–68.

Tews, J.; Brose, U.; Grimm, V.; Tielbörger, K.; Wichmann, M.C.; Schwager, M.; Jeltsch, F. 2004. Animal

species diversity driven by habitat heterogeneity/diversity: the importance of keystone

structures. Journal of Biogeography, 31(1): 79–92.

Tikuka, M.M. 2012. Geoarqueologia e paleohidrologia da planície aluvial holocênica do rio Madeira entre

Porto Velho e Abunã/RO. Amazonica: Revista de Antropologia, 4: 252–257.

Tuomisto, H.; Ruokolainen, K. 1997. The role of ecological knowledge in explaining biogeography and

biodiversity in Amazonia. Biodiversity and Conservation, 6: 347–357.

Turci, L.C.B.; Bernarde, P.S. 2008. Levantamento herpetofaunístico em uma localidade no município de

Cacoal, Rondônia, Brasil. Bioikos, 22: 101–108.

UFAM/DNIT. 2009. Estudo de impacto ambiental EIA–RIMA – BR–319 (km 250,0/655,7) – Meio Biótico.

Terceira edição. Amazonas, Brasil. (http://licenciamento.ibama.gov.br/Rodovias/ Vol. 3 Meio Biótico

> Vol). Acesso: 22/11/18.

Vellend, M. 2010. Conceptual synthesis in community ecology. The Quarterly Review Biology, 85: 183–

206.

Vernes, K.; Pope, L.C.; Hill, C.J.; Bärlocher, F. 2005. Seasonality, dung specificity and competition in dung

beetle assemblages in the Australian Wet Tropics, north–eastern Australia. Journal of Tropical

Ecology, 21(1): 1–8.

Vitt, L.J. 1991. Ecology and life history of the wide–foraging lizard Kentropyx calcarata (Teiidae) in

Amazonian Brazil. Canadian Journal of Zoology, 69(11): 2791–2799.

145

Vitt, L.J. 1996. Biodiversity of Amazonian lizards. In: Gibson, A.C. (Ed). Neotropical biodiversity and

conservation.Vol. 1. Miscellaneos publication, Mildred e Mathias Botanical Garden, University of

California, Los Angeles, USA. p. 89–108.

Vitt, L.J. 2000. Ecological consequences of body size in neonatal and small–bodied lizards in the neotropics.

Herpetological Monographs, 14: 388–400.

Vitt, L.J.; Blackburn, D.G. 1991. Ecology and life history of the viviparous lizard Mabuya bistriata

(Scincidae) in the Brazilian Amazon. Copeia, 12: 916–927.

Vitt, L.J.; Blackburn, D.G. 1999. Ecology and life history of the viviparous lizard Mabuya bistriata

(Scincidae) in the Brazilian Amazon. Copeia, 916–927.

Vitt, L.J.; Carvalho, C.M.D. 1992. Life in the trees: the ecology and life history of Kentropyx striatus

(Teiidae) in the Lavrado area of Roraima, Brazil, with comments on the life histories of tropical teiid

lizards. Canadian Journal of Zoology, 70(10): 1995–2006.

Vitt, L.J.; Colli, G.R.; Caldwell, J.P.; Mesquita, D.O.; Garda, A.A.; França, F.G. 2007. Detecting variation

in microhabitat use in low–diversity lizard assemblages across small–scale habitat gradients. Journal

of Herpetology, 41(4): 654–663.

Vitt, L.J.; Magnusson, W.E.; Avila–Pires T.C.S.; Lima. A.P. 2008. Guia de lagartos da Reserva Adolpho

Ducke, Amazônia Central. Áttema DesignEditorial, Manaus, Amazonas. 176 p.

Vitt, L.J.; Sartorius, S.S.; Avila–Pires, T.C.S.; Esposito, M.C.; Miles, D.B. 2000. Niche segregation among

sympatric Amazonian teiid lizards. Oecologia, 122(3): 410–420.

Vitt, L.J.; Zani, P.A. Espósito, M.C. 1999. Historical ecology of Amazonian lizards: implications for

community ecology. Oikos, 87: 286–294.

Vitt, L.J.; Zani, P.A.; Lima, A.P. 1997. Heliotherms in tropical rain forest: the ecology of Kentropyx

calcarata (Teiidae) and Mabuya nigropunctata (Scincidae) in the Curuá–Una of Brazil. Journal

Tropical Ecology, 13: 199–220.

Waldez, F.; Menin, M.; Vogt, R.C. 2013. Diversity of amphibians and Squamata reptilians from lower Purus

River Basin, Central Amazonia, Brazil. Biota Neotropica, 13(1): 300–316.

146

Wallace, A.R. 1852. On the monkeys of the Amazon. Proceedings of the Zoological Society of London, UK.

454pp.

Webb, J.K.; Shine, R. 1997. Out on a limb: conservation implications of tree–hollow use by a threatened

snake species (Hoplocephalus bungaroides: Serpentes, Elapidae). Biological Conservation, 81(12):

21–33.

Werneck, F.P.; Colli, G.R. 2006. The lizard assemblage from Seasonally Dry Tropical Forest enclaves in the

Cerrado biome, Brazil, and its association with the Pleistocenic Arc. Journal of Biogeography, 33(11):

1983–1992.

Werneck, F.P.; Colli, G.R.; Vitt, L.J. 2009. Determinants of assemblage structure in Neotropical dry forest

lizards. Austral Ecology, 34: 97–115.

Wesselingh, F.P.; Hoorn, C.; Kroonenberg, S.B.; Antonelli, A.; Lundberg, J.G.; Vonhof, H.B.;

Hooghiemstra, H. 2010. On the origin of Amazonian landscapes and biodiversity: a synthesis. In:

Hoorn, C.; Wesselingh, F. (Eds). Amazonia: Landscape and Species Evolution: A look into the past.

Vol. 1. John Wiley & Sons Ltd, Oxford, UK. p. 419–431.

Wiens, J.J.; Pyron, R.A.; Moen, D.S. 2011. Phylogenetic origins of local‐scale diversity patterns and the

causes of Amazonian megadiversity. Ecology letters, 14(7): 643–652.

Woinarski, J.C.Z.; Fisher, A.; Milne, D. 1999. Distribution patterns of vertebrates in relation to an extensive

rainfall gradient and variation in soil texture in the tropical savannas of the Northern Territory,

Australia. Journal of tropical ecology, 15(4): 381–398.

Wüster, W.; Ferguson, J.E.; Quijada–Mascareñas, A.; Pook, C.E.; Salomão, M.G.; Thorpe, R.S. 2005.

Tracing an invasion: land bridges, refugia, and phylogeography of the Neotropical rattlesnake

(Serpentes: Viperidae: Crotalus durissus). Molecular Ecology, 14: 1095–1108.

Ximenes, A.C. 2008. Mapas auto–organizáveis para a identificação de ecorregiões no interflúvio Madeira–

Purus: uma abordagem da biogeografia ecológica. Dissertação de mestrado, Instituto Nacional de

Pesquisas Espaciais, São José dos Campos, São Paulo. 155pp.

Yom-Tov, Y.; Geffen, E. 2006. Geographic variation in body size: the effects of ambient temperature and

precipitation. Oecologia, 148(2): 213–218. 147

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